{ "cells": [ { "cell_type": "markdown", "id": "640f2f18", "metadata": {}, "source": [ "# Practice: Chp. 13" ] }, { "cell_type": "code", "execution_count": 1, "id": "9b9954ef", "metadata": {}, "outputs": [], "source": [ "source(\"iplot.R\")\n", "suppressPackageStartupMessages(library(rethinking))" ] }, { "cell_type": "markdown", "id": "b340ae34", "metadata": {}, "source": [ "**13E1.** Which of the following priors will produce more *shrinkage* in the estimates?\n", "\n", "(a) $\\alpha_{tank} \\sim Normal(0,1)$\n", "\n", "(b) $\\alpha_{tank} \\sim Normal(0,2)$\n", "\n", "**Answer.** We could interpret this question in two ways. The first is that the author meant to\n", "write:\n", "\n", "(a) $\\bar{\\alpha} \\sim Normal(0,1)$\n", "\n", "(b) $\\bar{\\alpha} \\sim Normal(0,2)$\n", "\n", "That is, interpretion #1 is that these are priors for the hyperparameter for the average of all\n", "tanks, with no new prior specified for the hyperparameter for the variability among tanks $\\sigma$.\n", "\n", "The second interpretation is that the author is trying to express in shorthand new priors for both\n", "the $\\bar{\\alpha}$ and $\\sigma$ priors, and only the expected value of these two priors, ignoring\n", "a standard deviation. To use the same terms as the chapter:\n", "\n", "(a) $\\alpha_{tank} \\sim Normal(\\bar{\\alpha},\\sigma),\n", " \\bar{\\alpha} \\sim Normal(0,?),\n", " \\sigma \\sim Exponential(1)$\n", "\n", "(b) $\\alpha_{tank} \\sim Normal(\\bar{\\alpha},\\sigma),\n", " \\bar{\\alpha} \\sim Normal(0,?),\n", " \\sigma \\sim Exponential(\\frac{1}{2})$\n", "\n", "Notice we decrease the $\\lambda$ parameter to the exponential distribution to increase the expected\n", "value.\n", "\n", "Said another way, the first interpretation is that the author meant to specify this prior at the\n", "second level of the model, and the second interpretation is that the author meant to specify this\n", "prior at the first level. The first interpretation makes sense given this prior shows up directly in\n", "models in the chapter already, without much reinterpretation. The second interpretation is supported\n", "by the author's choice of variable name (e.g. see the chapter and question **13M3**). See also\n", "question **13M5**.\n", "\n", "In both interpretations, prior (a) will produce more shrinkage because it is more regularizing. It\n", "has a smaller standard deviation and therefore expects less variability.\n", "\n", "**13E2.** Rewrite the following model as a multilevel model.\n", "\n", "$$\n", "\\begin{align}\n", "y_i & \\sim Binomial(1,p_i) \\\\\n", "logit(p_i) & = \\alpha_{group[i]} + \\beta x_i \\\\\n", "\\alpha_{group} & \\sim Normal(0, 1.5) \\\\\n", "\\beta & \\sim Normal(0, 0.5)\n", "\\end{align}\n", "$$\n", "\n", "**Answer.** The focus of this chapter is on varying intercepts rather than varying effects (see the next\n", "chapter), so we'll only convert the intercept:\n", "\n", "$$\n", "\\begin{align}\n", "y_i & \\sim Binomial(1,p_i) \\\\\n", "logit(p_i) & = \\alpha_{group[i]} + \\beta x_i \\\\\n", "\\alpha_{group} & \\sim Normal(\\bar{\\alpha}, \\sigma) \\\\\n", "\\bar{\\alpha} & \\sim Normal(0, 1.5) \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta & \\sim Normal(0, 0.5)\n", "\\end{align}\n", "$$\n", "\n", "**13E3.** Rewrite the following model as a multilevel model.\n", "\n", "$$\n", "\\begin{align}\n", "y_i & \\sim Normal(\\mu_i,\\sigma) \\\\\n", "\\mu_i & = \\alpha_{group[i]} + \\beta x_i \\\\\n", "\\alpha_{group} & \\sim Normal(0, 5) \\\\\n", "\\beta & \\sim Normal(0, 1) \\\\\n", "\\sigma & \\sim Exponential(1)\n", "\\end{align}\n", "$$\n", "\n", "**Answer.** As in the last question, we'll only convert the intercept:\n", "\n", "$$\n", "\\begin{align}\n", "y_i & \\sim Normal(\\mu_i,\\sigma_1) \\\\\n", "\\mu_i & = \\alpha_{group[i]} + \\beta x_i \\\\\n", "\\alpha_{group} & \\sim Normal(\\bar{\\alpha}, \\sigma_2) \\\\\n", "\\bar{\\alpha} & \\sim Normal(0, 5) \\\\\n", "\\sigma_2 & \\sim Exponential\\left(\\frac{1}{2}\\right) \\\\\n", "\\beta & \\sim Normal(0, 1) \\\\\n", "\\sigma_1 & \\sim Exponential(1)\n", "\\end{align}\n", "$$\n", "\n", "**13E4.** Write a mathematical model formula for a Poisson regression with varying intercepts.\n", "\n", "$$\n", "\\begin{align}\n", "y_i & \\sim Poisson(\\lambda) \\\\\n", "log(\\lambda) & = \\alpha_{group[i]} \\\\\n", "\\alpha_{group} & \\sim Normal(\\bar{\\alpha}, \\sigma) \\\\\n", "\\bar{\\alpha} & \\sim Normal(0, 5) \\\\\n", "\\sigma & \\sim Exponential(1)\n", "\\end{align}\n", "$$\n", "\n", "**13E5.** Write a mathematical model formula for a Poisson regression with two different kinds of\n", "varying intercepts, a cross-classified model.\n", "\n", "$$\n", "\\begin{align}\n", "y_i & \\sim Poisson(\\lambda) \\\\\n", "log(\\lambda) & = \\alpha_{x[i]} + \\alpha_{y[i]} \\\\\n", "\\alpha_{x} & \\sim Normal(\\mu_x, \\sigma_x) \\\\\n", "\\mu_x & \\sim Normal(0, 5) \\\\\n", "\\sigma_x & \\sim Exponential(1) \\\\\n", "\\alpha_{y} & \\sim Normal(0, \\sigma_y) \\\\\n", "\\sigma_y & \\sim Exponential(1)\n", "\\end{align}\n", "$$\n", "\n", "**13M1.** Revisit the Reed frog survival data, `data(reedfrogs)`, and add the `predation` and `size`\n", "treatment variables to the varying intercept model. Consider models with either main effect alone,\n", "both main effects, as well as a model including both and their interaction. Instead of focusing on\n", "inferences about these two predictor variables, focus on the inferred variation across tanks.\n", "Explain why it changes as it does across models.\n", "\n", "**ERROR.** The `predation` predictor is actually labeled `pred`.\n", "\n", "**ERROR.** The author duplicated this question in **13H4**, without realizing he had moved it and\n", "primarily only changed wording.\n", "\n", "Compare the second sentences:\n", "\n", "> Consider models with either main effect alone, both main effects, as well as a model including both\n", "> and their interaction.\n", "\n", "> Consider models with either predictor alone, both predictors, as well as a model including their\n", "> interaction.\n", "\n", "One sentence only exists in **13H4**:\n", "\n", "> What do you infer about the causal inference of these predictor variables?\n", "\n", "Compare the last two sentences:\n", "\n", "> Instead of focusing on inferences about these two predictor variables, focus on the inferred\n", "> variation across tanks. Explain why it changes as it does across models.\n", "\n", "> Also focus on the inferred variation across tanks (the $\\sigma$ across tanks). Explain why it\n", "> changes as it does across models with different predictors included.\n", "\n", "We could treat **13H4** as a separate question that expands on **13M1** by adding causal inference,\n", "but this answer will combine the two.\n", "\n", "**Answer.** First, let's reproduce results from model `m13.2` in the chapter:" ] }, { "cell_type": "code", "execution_count": 2, "id": "7aaf6a11", "metadata": {}, "outputs": [ { "data": { "image/png": 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ELgl9xABWgA0wyCA1SA4NAMggNUgOpAzSA4QAVoANMMggNUgODQDIIDVEBeHbit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\nAElFTkSuQmCC" }, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_3_0.png" } }, "output_type": "display_data" } ], "source": [ "data(reedfrogs)\n", "rf_df <- reedfrogs\n", "rf_df$tank <- 1:nrow(rf_df)\n", "\n", "rf_dat <- list(\n", " S = rf_df$surv,\n", " N = rf_df$density,\n", " tank = rf_df$tank\n", ")\n", "\n", "## R code 13.3\n", "m13.2 <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank],\n", " a[tank] ~ dnorm(a_bar, sigma),\n", " a_bar ~ dnorm(0, 1.5),\n", " sigma ~ dexp(1)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE\n", ")\n", "\n", "iplot(function() {\n", " plot(precis(m13.2, depth=2), main='m13.2')\n", "}, ar=1.0)" ] }, { "cell_type": "markdown", "id": "2b285a33", "metadata": {}, "source": [ "Raw data (preceding plot):" ] }, { "cell_type": "code", "execution_count": 3, "id": "7dae40c3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff Rhat4 \n", "a[1] 2.123895005 0.8800029 0.88324287 3.60357846 3135.042 0.9993171\n", "a[2] 3.069417613 1.0879816 1.53213514 4.97198488 2880.482 0.9991000\n", "a[3] 1.025435079 0.6859747 -0.01876991 2.11478208 4086.947 0.9992862\n", "a[4] 3.045003704 1.0904417 1.44463933 4.93253177 3026.895 0.9986501\n", "a[5] 2.133584064 0.8865480 0.82569033 3.69185945 3242.085 0.9996229\n", "a[6] 2.129875960 0.8622741 0.85550909 3.51833473 4101.535 0.9983410\n", "a[7] 3.042309196 1.0803602 1.50263737 4.89527573 3300.782 0.9992896\n", "a[8] 2.143396095 0.8774313 0.87912951 3.65976593 4755.805 0.9987193\n", "a[9] -0.181523811 0.6239130 -1.20279368 0.81605579 3355.371 0.9989467\n", "a[10] 2.160446881 0.8868395 0.90286995 3.69858829 2919.991 1.0002489\n", "a[11] 0.982944595 0.6409224 -0.01787153 2.03912637 4340.708 0.9989579\n", "a[12] 0.587181118 0.6201083 -0.37215354 1.60414730 5487.450 0.9985093\n", "a[13] 1.013060494 0.6513388 0.04314274 2.09267998 4561.709 0.9991331\n", "a[14] 0.208921393 0.5888650 -0.77247363 1.13103679 3773.708 0.9990913\n", "a[15] 2.112968097 0.8671883 0.85145433 3.61051924 4976.691 0.9991278\n", "a[16] 2.153449499 0.9001026 0.84944705 3.64511067 3623.187 0.9985997\n", "a[17] 2.922906230 0.8207311 1.72786343 4.31192056 2727.910 1.0017675\n", "a[18] 2.391108593 0.6594986 1.42438049 3.46904519 3825.827 0.9988642\n", "a[19] 2.016368646 0.5883191 1.14001978 3.00910079 4198.075 0.9993717\n", "a[20] 3.696619684 1.0349830 2.22233524 5.54831067 2697.947 0.9997244\n", "a[21] 2.392176052 0.6338009 1.49698276 3.49281857 3195.078 0.9992764\n", "a[22] 2.380392651 0.6348463 1.44870379 3.44691853 3352.341 0.9986587\n", "a[23] 2.387766858 0.6677886 1.38891610 3.52825066 3481.055 0.9992638\n", "a[24] 1.707655898 0.5241377 0.91766718 2.60417300 5142.443 0.9981182\n", "a[25] -0.991016689 0.4439675 -1.72522983 -0.28233503 4224.010 0.9982751\n", "a[26] 0.162679937 0.3803444 -0.44872939 0.76593787 5110.381 0.9991206\n", "a[27] -1.428071502 0.4897130 -2.22955461 -0.68573472 3306.490 0.9985784\n", "a[28] -0.470549934 0.4166839 -1.15849296 0.19914758 4359.714 0.9992520\n", "a[29] 0.156650932 0.4082734 -0.48325866 0.81498354 3888.688 0.9992465\n", "a[30] 1.441025015 0.4863160 0.70097745 2.24540124 3645.397 0.9990923\n", "a[31] -0.633425518 0.4092424 -1.29825277 0.01788939 3807.050 0.9988602\n", "a[32] -0.307137176 0.4049534 -0.96427001 0.31531593 4200.218 0.9989423\n", "a[33] 3.196570698 0.7447295 2.10154436 4.49980149 2880.864 0.9990879\n", "a[34] 2.712794013 0.6433201 1.74888220 3.78643188 3095.331 0.9988198\n", "a[35] 2.731620944 0.6664324 1.77676015 3.83311873 2992.938 0.9990613\n", "a[36] 2.051060489 0.5000432 1.28411900 2.86453520 3690.270 0.9992633\n", "a[37] 2.065591183 0.5017172 1.30591712 2.92647140 3638.510 0.9989189\n", "a[38] 3.891461657 0.9699415 2.47805339 5.58549440 2735.887 1.0004954\n", "a[39] 2.705455255 0.6495701 1.77860035 3.84518415 2741.298 0.9996879\n", "a[40] 2.354011311 0.5506689 1.50543484 3.26092214 4252.637 0.9991978\n", "a[41] -1.799497041 0.4835684 -2.57131168 -1.07337199 3708.538 0.9989449\n", "a[42] -0.576316697 0.3417616 -1.12795518 -0.03377259 5124.122 0.9981467\n", "a[43] -0.450266837 0.3399222 -0.99046630 0.08640756 5109.116 0.9986930\n", "a[44] -0.333124738 0.3317197 -0.84461886 0.18941723 2979.151 0.9985858\n", "a[45] 0.585451130 0.3402349 0.04255837 1.14995230 4701.920 0.9993146\n", "a[46] -0.569382107 0.3518077 -1.14556430 -0.01996810 6426.916 0.9987633\n", "a[47] 2.070103142 0.5140356 1.30579740 2.93810996 3331.361 0.9987141\n", "a[48] -0.002109234 0.3203171 -0.52018692 0.50742515 3988.177 0.9981734\n", "a_bar 1.346620398 0.2500101 0.96140376 1.74271963 3215.743 0.9989353\n", "sigma 1.610600906 0.2106371 1.30392541 1.97048034 1805.981 1.0002795" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(precis(m13.2, depth = 2), mimetypes=\"text/plain\")\n", "\n", "rf_df$Predator <- as.integer(as.factor(rf_df$pred))\n", "rf_df$Size <- as.integer(as.factor(rf_df$size))\n", "rf_df$Treatment <- 1 + ifelse(rf_df$Predator == 1, 0, 1) + 2*ifelse(rf_df$Size == 1, 0, 1)" ] }, { "cell_type": "markdown", "id": "2a3d8030", "metadata": {}, "source": [ "The `reedfrogs` data.frame is small enough to show in its entirety. Notice several new preprocessed\n", "variables (columns) this solution will introduce later as they are used in models:" ] }, { "cell_type": "code", "execution_count": 4, "id": "ea9822fa", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
A data.frame: 48 × 9
densitypredsizesurvpropsurvtankPredatorSizeTreatment
<int><fct><fct><int><dbl><int><int><int><dbl>
10no big 90.9000000 1111
10no big 101.0000000 2111
10no big 70.7000000 3111
10no big 101.0000000 4111
10no small 90.9000000 5123
10no small 90.9000000 6123
10no small101.0000000 7123
10no small 90.9000000 8123
10predbig 40.4000000 9212
10predbig 90.900000010212
10predbig 70.700000011212
10predbig 60.600000012212
10predsmall 70.700000013224
10predsmall 50.500000014224
10predsmall 90.900000015224
10predsmall 90.900000016224
25no big 240.960000017111
25no big 230.920000018111
25no big 220.880000019111
25no big 251.000000020111
25no small230.920000021123
25no small230.920000022123
25no small230.920000023123
25no small210.840000024123
25predbig 60.240000025212
25predbig 130.520000026212
25predbig 40.160000027212
25predbig 90.360000028212
25predsmall130.520000029224
25predsmall200.800000030224
25predsmall 80.320000031224
25predsmall100.400000032224
35no big 340.971428633111
35no big 330.942857134111
35no big 330.942857135111
35no big 310.885714336111
35no small310.885714337123
35no small351.000000038123
35no small330.942857139123
35no small320.914285740123
35predbig 40.114285741212
35predbig 120.342857142212
35predbig 130.371428643212
35predbig 140.400000044212
35predsmall220.628571445224
35predsmall120.342857146224
35predsmall310.885714347224
35predsmall170.485714348224
\n" ], "text/latex": [ "A data.frame: 48 × 9\n", "\\begin{tabular}{lllllllll}\n", " density & pred & size & surv & propsurv & tank & Predator & Size & Treatment\\\\\n", " & & & & & & & & \\\\\n", "\\hline\n", "\t 10 & no & big & 9 & 0.9000000 & 1 & 1 & 1 & 1\\\\\n", "\t 10 & no & big & 10 & 1.0000000 & 2 & 1 & 1 & 1\\\\\n", "\t 10 & no & big & 7 & 0.7000000 & 3 & 1 & 1 & 1\\\\\n", "\t 10 & no & big & 10 & 1.0000000 & 4 & 1 & 1 & 1\\\\\n", "\t 10 & no & small & 9 & 0.9000000 & 5 & 1 & 2 & 3\\\\\n", "\t 10 & no & small & 9 & 0.9000000 & 6 & 1 & 2 & 3\\\\\n", "\t 10 & no & small & 10 & 1.0000000 & 7 & 1 & 2 & 3\\\\\n", "\t 10 & no & small & 9 & 0.9000000 & 8 & 1 & 2 & 3\\\\\n", "\t 10 & pred & big & 4 & 0.4000000 & 9 & 2 & 1 & 2\\\\\n", "\t 10 & pred & big & 9 & 0.9000000 & 10 & 2 & 1 & 2\\\\\n", "\t 10 & pred & big & 7 & 0.7000000 & 11 & 2 & 1 & 2\\\\\n", "\t 10 & pred & big & 6 & 0.6000000 & 12 & 2 & 1 & 2\\\\\n", "\t 10 & pred & small & 7 & 0.7000000 & 13 & 2 & 2 & 4\\\\\n", "\t 10 & pred & small & 5 & 0.5000000 & 14 & 2 & 2 & 4\\\\\n", "\t 10 & pred & small & 9 & 0.9000000 & 15 & 2 & 2 & 4\\\\\n", "\t 10 & pred & small & 9 & 0.9000000 & 16 & 2 & 2 & 4\\\\\n", "\t 25 & no & big & 24 & 0.9600000 & 17 & 1 & 1 & 1\\\\\n", "\t 25 & no & big & 23 & 0.9200000 & 18 & 1 & 1 & 1\\\\\n", "\t 25 & no & big & 22 & 0.8800000 & 19 & 1 & 1 & 1\\\\\n", "\t 25 & no & big & 25 & 1.0000000 & 20 & 1 & 1 & 1\\\\\n", "\t 25 & no & small & 23 & 0.9200000 & 21 & 1 & 2 & 3\\\\\n", "\t 25 & no & small & 23 & 0.9200000 & 22 & 1 & 2 & 3\\\\\n", "\t 25 & no & small & 23 & 0.9200000 & 23 & 1 & 2 & 3\\\\\n", "\t 25 & no & small & 21 & 0.8400000 & 24 & 1 & 2 & 3\\\\\n", "\t 25 & pred & big & 6 & 0.2400000 & 25 & 2 & 1 & 2\\\\\n", "\t 25 & pred & big & 13 & 0.5200000 & 26 & 2 & 1 & 2\\\\\n", "\t 25 & pred & big & 4 & 0.1600000 & 27 & 2 & 1 & 2\\\\\n", "\t 25 & pred & big & 9 & 0.3600000 & 28 & 2 & 1 & 2\\\\\n", "\t 25 & pred & small & 13 & 0.5200000 & 29 & 2 & 2 & 4\\\\\n", "\t 25 & pred & small & 20 & 0.8000000 & 30 & 2 & 2 & 4\\\\\n", "\t 25 & pred & small & 8 & 0.3200000 & 31 & 2 & 2 & 4\\\\\n", "\t 25 & pred & small & 10 & 0.4000000 & 32 & 2 & 2 & 4\\\\\n", "\t 35 & no & big & 34 & 0.9714286 & 33 & 1 & 1 & 1\\\\\n", "\t 35 & no & big & 33 & 0.9428571 & 34 & 1 & 1 & 1\\\\\n", "\t 35 & no & big & 33 & 0.9428571 & 35 & 1 & 1 & 1\\\\\n", "\t 35 & no & big & 31 & 0.8857143 & 36 & 1 & 1 & 1\\\\\n", "\t 35 & no & small & 31 & 0.8857143 & 37 & 1 & 2 & 3\\\\\n", "\t 35 & no & small & 35 & 1.0000000 & 38 & 1 & 2 & 3\\\\\n", "\t 35 & no & small & 33 & 0.9428571 & 39 & 1 & 2 & 3\\\\\n", "\t 35 & no & small & 32 & 0.9142857 & 40 & 1 & 2 & 3\\\\\n", "\t 35 & pred & big & 4 & 0.1142857 & 41 & 2 & 1 & 2\\\\\n", "\t 35 & pred & big & 12 & 0.3428571 & 42 & 2 & 1 & 2\\\\\n", "\t 35 & pred & big & 13 & 0.3714286 & 43 & 2 & 1 & 2\\\\\n", "\t 35 & pred & big & 14 & 0.4000000 & 44 & 2 & 1 & 2\\\\\n", "\t 35 & pred & small & 22 & 0.6285714 & 45 & 2 & 2 & 4\\\\\n", "\t 35 & pred & small & 12 & 0.3428571 & 46 & 2 & 2 & 4\\\\\n", "\t 35 & pred & small & 31 & 0.8857143 & 47 & 2 & 2 & 4\\\\\n", "\t 35 & pred & small & 17 & 0.4857143 & 48 & 2 & 2 & 4\\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "A data.frame: 48 × 9\n", "\n", "| density <int> | pred <fct> | size <fct> | surv <int> | propsurv <dbl> | tank <int> | Predator <int> | Size <int> | Treatment <dbl> |\n", "|---|---|---|---|---|---|---|---|---|\n", "| 10 | no | big | 9 | 0.9000000 | 1 | 1 | 1 | 1 |\n", "| 10 | no | big | 10 | 1.0000000 | 2 | 1 | 1 | 1 |\n", "| 10 | no | big | 7 | 0.7000000 | 3 | 1 | 1 | 1 |\n", "| 10 | no | big | 10 | 1.0000000 | 4 | 1 | 1 | 1 |\n", "| 10 | no | small | 9 | 0.9000000 | 5 | 1 | 2 | 3 |\n", "| 10 | no | small | 9 | 0.9000000 | 6 | 1 | 2 | 3 |\n", "| 10 | no | small | 10 | 1.0000000 | 7 | 1 | 2 | 3 |\n", "| 10 | no | small | 9 | 0.9000000 | 8 | 1 | 2 | 3 |\n", "| 10 | pred | big | 4 | 0.4000000 | 9 | 2 | 1 | 2 |\n", "| 10 | pred | big | 9 | 0.9000000 | 10 | 2 | 1 | 2 |\n", "| 10 | pred | big | 7 | 0.7000000 | 11 | 2 | 1 | 2 |\n", "| 10 | pred | big | 6 | 0.6000000 | 12 | 2 | 1 | 2 |\n", "| 10 | pred | small | 7 | 0.7000000 | 13 | 2 | 2 | 4 |\n", "| 10 | pred | small | 5 | 0.5000000 | 14 | 2 | 2 | 4 |\n", "| 10 | pred | small | 9 | 0.9000000 | 15 | 2 | 2 | 4 |\n", "| 10 | pred | small | 9 | 0.9000000 | 16 | 2 | 2 | 4 |\n", "| 25 | no | big | 24 | 0.9600000 | 17 | 1 | 1 | 1 |\n", "| 25 | no | big | 23 | 0.9200000 | 18 | 1 | 1 | 1 |\n", "| 25 | no | big | 22 | 0.8800000 | 19 | 1 | 1 | 1 |\n", "| 25 | no | big | 25 | 1.0000000 | 20 | 1 | 1 | 1 |\n", "| 25 | no | small | 23 | 0.9200000 | 21 | 1 | 2 | 3 |\n", "| 25 | no | small | 23 | 0.9200000 | 22 | 1 | 2 | 3 |\n", "| 25 | no | small | 23 | 0.9200000 | 23 | 1 | 2 | 3 |\n", "| 25 | no | small | 21 | 0.8400000 | 24 | 1 | 2 | 3 |\n", "| 25 | pred | big | 6 | 0.2400000 | 25 | 2 | 1 | 2 |\n", "| 25 | pred | big | 13 | 0.5200000 | 26 | 2 | 1 | 2 |\n", "| 25 | pred | big | 4 | 0.1600000 | 27 | 2 | 1 | 2 |\n", "| 25 | pred | big | 9 | 0.3600000 | 28 | 2 | 1 | 2 |\n", "| 25 | pred | small | 13 | 0.5200000 | 29 | 2 | 2 | 4 |\n", "| 25 | pred | small | 20 | 0.8000000 | 30 | 2 | 2 | 4 |\n", "| 25 | pred | small | 8 | 0.3200000 | 31 | 2 | 2 | 4 |\n", "| 25 | pred | small | 10 | 0.4000000 | 32 | 2 | 2 | 4 |\n", "| 35 | no | big | 34 | 0.9714286 | 33 | 1 | 1 | 1 |\n", "| 35 | no | big | 33 | 0.9428571 | 34 | 1 | 1 | 1 |\n", "| 35 | no | big | 33 | 0.9428571 | 35 | 1 | 1 | 1 |\n", "| 35 | no | big | 31 | 0.8857143 | 36 | 1 | 1 | 1 |\n", "| 35 | no | small | 31 | 0.8857143 | 37 | 1 | 2 | 3 |\n", "| 35 | no | small | 35 | 1.0000000 | 38 | 1 | 2 | 3 |\n", "| 35 | no | small | 33 | 0.9428571 | 39 | 1 | 2 | 3 |\n", "| 35 | no | small | 32 | 0.9142857 | 40 | 1 | 2 | 3 |\n", "| 35 | pred | big | 4 | 0.1142857 | 41 | 2 | 1 | 2 |\n", "| 35 | pred | big | 12 | 0.3428571 | 42 | 2 | 1 | 2 |\n", "| 35 | pred | big | 13 | 0.3714286 | 43 | 2 | 1 | 2 |\n", "| 35 | pred | big | 14 | 0.4000000 | 44 | 2 | 1 | 2 |\n", "| 35 | pred | small | 22 | 0.6285714 | 45 | 2 | 2 | 4 |\n", "| 35 | pred | small | 12 | 0.3428571 | 46 | 2 | 2 | 4 |\n", "| 35 | pred | small | 31 | 0.8857143 | 47 | 2 | 2 | 4 |\n", "| 35 | pred | small | 17 | 0.4857143 | 48 | 2 | 2 | 4 |\n", "\n" ], "text/plain": [ " density pred size surv propsurv tank Predator Size Treatment\n", "1 10 no big 9 0.9000000 1 1 1 1 \n", "2 10 no big 10 1.0000000 2 1 1 1 \n", "3 10 no big 7 0.7000000 3 1 1 1 \n", "4 10 no big 10 1.0000000 4 1 1 1 \n", "5 10 no small 9 0.9000000 5 1 2 3 \n", "6 10 no small 9 0.9000000 6 1 2 3 \n", "7 10 no small 10 1.0000000 7 1 2 3 \n", "8 10 no small 9 0.9000000 8 1 2 3 \n", "9 10 pred big 4 0.4000000 9 2 1 2 \n", "10 10 pred big 9 0.9000000 10 2 1 2 \n", "11 10 pred big 7 0.7000000 11 2 1 2 \n", "12 10 pred big 6 0.6000000 12 2 1 2 \n", "13 10 pred small 7 0.7000000 13 2 2 4 \n", "14 10 pred small 5 0.5000000 14 2 2 4 \n", "15 10 pred small 9 0.9000000 15 2 2 4 \n", "16 10 pred small 9 0.9000000 16 2 2 4 \n", "17 25 no big 24 0.9600000 17 1 1 1 \n", "18 25 no big 23 0.9200000 18 1 1 1 \n", "19 25 no big 22 0.8800000 19 1 1 1 \n", "20 25 no big 25 1.0000000 20 1 1 1 \n", "21 25 no small 23 0.9200000 21 1 2 3 \n", "22 25 no small 23 0.9200000 22 1 2 3 \n", "23 25 no small 23 0.9200000 23 1 2 3 \n", "24 25 no small 21 0.8400000 24 1 2 3 \n", "25 25 pred big 6 0.2400000 25 2 1 2 \n", "26 25 pred big 13 0.5200000 26 2 1 2 \n", "27 25 pred big 4 0.1600000 27 2 1 2 \n", "28 25 pred big 9 0.3600000 28 2 1 2 \n", "29 25 pred small 13 0.5200000 29 2 2 4 \n", "30 25 pred small 20 0.8000000 30 2 2 4 \n", "31 25 pred small 8 0.3200000 31 2 2 4 \n", "32 25 pred small 10 0.4000000 32 2 2 4 \n", "33 35 no big 34 0.9714286 33 1 1 1 \n", "34 35 no big 33 0.9428571 34 1 1 1 \n", "35 35 no big 33 0.9428571 35 1 1 1 \n", "36 35 no big 31 0.8857143 36 1 1 1 \n", "37 35 no small 31 0.8857143 37 1 2 3 \n", "38 35 no small 35 1.0000000 38 1 2 3 \n", "39 35 no small 33 0.9428571 39 1 2 3 \n", "40 35 no small 32 0.9142857 40 1 2 3 \n", "41 35 pred big 4 0.1142857 41 2 1 2 \n", "42 35 pred big 12 0.3428571 42 2 1 2 \n", "43 35 pred big 13 0.3714286 43 2 1 2 \n", "44 35 pred big 14 0.4000000 44 2 1 2 \n", "45 35 pred small 22 0.6285714 45 2 2 4 \n", "46 35 pred small 12 0.3428571 46 2 2 4 \n", "47 35 pred small 31 0.8857143 47 2 2 4 \n", "48 35 pred small 17 0.4857143 48 2 2 4 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(rf_df)" ] }, { "cell_type": "markdown", "id": "4ca14626", "metadata": {}, "source": [ "The `help` is also short:" ] }, { "cell_type": "code", "execution_count": 5, "id": "46d23484", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
reedfrogs {rethinking}R Documentation
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Data on reed frog predation experiments

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Description

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Data on lab experiments on the density- and size-dependent\n", "predation rate of an African reed frog, Hyperolius\n", "spinigularis,\n", "from Vonesh and Bolker 2005 \n", "

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Usage

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data(reedfrogs)
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Format

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Various data with variables:\n", "

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\n", "
density

initial tadpole density (number of tadpoles\n", "in a 1.2 x 0.8 x 0.4 m tank) [experiment 1]

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pred

factor: predators present or absent [experiment 1]

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size

factor: big or small tadpoles [experiment 1]

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surv

number surviving

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propsurv

proportion surviving (=surv/density) [experiment 1]

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Source

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Vonesh and Bolker (2005) Compensatory larval responses shift\n", "trade-offs associated with predator-induced hatching plasticity.\n", "Ecology 86:1580-1591\n", "

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Examples

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\n",
       "data(reedfrogs)\n",
       "boxplot(propsurv~size*density*pred,data=reedfrogs)\n",
       "
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[Package rethinking version 2.13 ]
" ], "text/latex": [ "\\inputencoding{utf8}\n", "\\HeaderA{reedfrogs}{Data on reed frog predation experiments}{reedfrogs}\n", "\\keyword{datasets}{reedfrogs}\n", "%\n", "\\begin{Description}\\relax\n", "Data on lab experiments on the density- and size-dependent\n", "predation rate of an African reed frog, \\emph{Hyperolius\n", "spinigularis},\n", "from Vonesh and Bolker 2005 \n", "\\end{Description}\n", "%\n", "\\begin{Usage}\n", "\\begin{verbatim}\n", "data(reedfrogs)\n", "\\end{verbatim}\n", "\\end{Usage}\n", "%\n", "\\begin{Format}\n", "Various data with variables:\n", "\\begin{description}\n", "\n", "\\item[\\code{density}] initial tadpole density (number of tadpoles\n", "in a 1.2 x 0.8 x 0.4 m tank) [experiment 1]\n", "\\item[\\code{pred}] factor: predators present or absent [experiment 1]\n", "\\item[\\code{size}] factor: big or small tadpoles [experiment 1]\n", "\\item[\\code{surv}] number surviving\n", "\\item[\\code{propsurv}] proportion surviving (=surv/density) [experiment 1]\n", "\n", "\\end{description}\n", "\n", "\\end{Format}\n", "%\n", "\\begin{Source}\\relax\n", "Vonesh and Bolker (2005) Compensatory larval responses shift\n", "trade-offs associated with predator-induced hatching plasticity.\n", "Ecology 86:1580-1591\n", "\\end{Source}\n", "%\n", "\\begin{Examples}\n", "\\begin{ExampleCode}\n", "data(reedfrogs)\n", "boxplot(propsurv~size*density*pred,data=reedfrogs)\n", "\\end{ExampleCode}\n", "\\end{Examples}" ], "text/plain": [ "reedfrogs package:rethinking R Documentation\n", "\n", "_\bD_\ba_\bt_\ba _\bo_\bn _\br_\be_\be_\bd _\bf_\br_\bo_\bg _\bp_\br_\be_\bd_\ba_\bt_\bi_\bo_\bn _\be_\bx_\bp_\be_\br_\bi_\bm_\be_\bn_\bt_\bs\n", "\n", "_\bD_\be_\bs_\bc_\br_\bi_\bp_\bt_\bi_\bo_\bn:\n", "\n", " Data on lab experiments on the density- and size-dependent\n", " predation rate of an African reed frog, _Hyperolius spinigularis_,\n", " from Vonesh and Bolker 2005\n", "\n", "_\bU_\bs_\ba_\bg_\be:\n", "\n", " data(reedfrogs)\n", " \n", "_\bF_\bo_\br_\bm_\ba_\bt:\n", "\n", " Various data with variables:\n", "\n", " ‘density’ initial tadpole density (number of tadpoles in a 1.2 x\n", " 0.8 x 0.4 m tank) [experiment 1]\n", "\n", " ‘pred’ factor: predators present or absent [experiment 1]\n", "\n", " ‘size’ factor: big or small tadpoles [experiment 1]\n", "\n", " ‘surv’ number surviving\n", "\n", " ‘propsurv’ proportion surviving (=surv/density) [experiment 1]\n", "\n", "_\bS_\bo_\bu_\br_\bc_\be:\n", "\n", " Vonesh and Bolker (2005) Compensatory larval responses shift\n", " trade-offs associated with predator-induced hatching plasticity.\n", " Ecology 86:1580-1591\n", "\n", "_\bE_\bx_\ba_\bm_\bp_\bl_\be_\bs:\n", "\n", " data(reedfrogs)\n", " boxplot(propsurv~size*density*pred,data=reedfrogs)\n", " " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(help(reedfrogs))" ] }, { "cell_type": "markdown", "id": "e00e9416", "metadata": {}, "source": [ "Our first model will add the `pred` predictor on only the first level:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta_{pred[i]} \\\\\n", "\\alpha_j & \\sim Normal(\\bar{\\alpha}, \\sigma), j = 1..48 \\\\\n", "\\bar{\\alpha} & \\sim Normal(0, 1.5) \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta_j & \\sim Normal(0, 1.5), j = 1..2\n", "\\end{align}\n", "$$\n", "\n", "Seeing as this is a chapter on multilevel models, and it's generally advisable to consider a\n", "multilevel model when we have exchangeable index variables, should we add a second level of\n", "parameters for this predictor? In other words:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta_{pred[i]} \\\\\n", "\\alpha_j & \\sim Normal(\\bar{\\alpha}, \\sigma_{\\alpha}), j = 1..48 \\\\\n", "\\bar{\\alpha} & \\sim Normal(0, 1.5) \\\\\n", "\\sigma_{\\alpha} & \\sim Exponential(1) \\\\\n", "\\beta_j & \\sim Normal(0, \\sigma_{\\beta}), j = 1..2 \\\\\n", "\\sigma_{\\beta} & \\sim Exponential(1)\n", "\\end{align}\n", "$$\n", "\n", "The problem with this model is that there are only 2 (rather than 48) clusters for us to learn from,\n", "that is, we are adding one second-level parameter to go with only two first-level parameters. Said\n", "another way, do our clusters have anything to learn from each other? It may help to not forget about\n", "the last tank of tadpoles when learning about a new one, or the last chimp when learning about a new\n", "one, but in this case there is only one other pool to learn from: either all predator pools, or all\n", "non-predator pools.\n", "\n", "We could try to remember what we learned about one predator pool when moving to another predator\n", "pool. In this approach, we would learn one $\\bar{\\alpha}$ and one $\\sigma$ for the predator pools,\n", "and one $\\bar{\\alpha}$ and one $\\sigma$ for the non-predator pools. Presumably this would require\n", "reindexing predator and non-predator pools from 1..24. The original model from the chapter already\n", "has an intercept for individual pools this approach would likely not differ significantly from, so\n", "we will avoid these complications and only add `pred` on the first level.\n", "\n", "Now let's fit our new model, with a `pred` predictor on the first level. This model struggles to fit\n", "as provided above. To avoid Stan warnings about RHat, Bulk ESS, and Tail ESS, we're actually going\n", "to fit a model with a different $\\bar{\\alpha}$ prior than the one proposed above:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta_{pred[i]} \\\\\n", "\\alpha_j & \\sim Normal(\\bar{\\alpha}, \\sigma), j = 1..48 \\\\\n", "\\bar{\\alpha} & \\sim Normal(0, 0.1) \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta_j & \\sim Normal(0, 1.5), j = 1..2\n", "\\end{align}\n", "$$\n", "\n", "See more comments on this tight $\\bar{\\alpha}$ prior below." ] }, { "cell_type": "code", "execution_count": 6, "id": "56c474d7", "metadata": {}, "outputs": [ { "data": { "image/png": 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A6CfIAJIA7VgTiACSAO1UECGDABxKE6SAADJoA4VIc8ASx3bL2w5M7rkAAmNRCH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\n7IY6OnAU231uM4hDWvwVx7219a+kX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}, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_11_0.png" } }, "output_type": "display_data" } ], "source": [ "rf_dat <- list(\n", " S = rf_df$surv,\n", " N = rf_df$density,\n", " tank = rf_df$tank,\n", " Predator = rf_df$Predator\n", ")\n", "\n", "m_rf_pred_orig <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank] + bPredator[Predator],\n", " a[tank] ~ dnorm(a_bar, sigma),\n", " a_bar ~ dnorm(0, 0.1),\n", " sigma ~ dexp(1),\n", " bPredator[Predator] ~ dnorm(0, 1.5)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE, iter=2000\n", ")\n", "\n", "iplot(function() {\n", " plot(precis(m_rf_pred_orig, depth=2), main='m_rf_pred_orig')\n", "}, ar=1.0)" ] }, { "cell_type": "markdown", "id": "1a13b82c", "metadata": {}, "source": [ "Raw data (preceding plot):" ] }, { "cell_type": "code", "execution_count": 7, "id": "b082360c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff Rhat4 \n", "a[1] -0.091053566 0.67733826 -1.1619387 1.00363590 5706.8320 0.9992140\n", "a[2] 0.405284429 0.72231669 -0.6835375 1.63240635 4280.2961 0.9999209\n", "a[3] -0.893632468 0.65422903 -1.9246907 0.14803434 3835.9654 1.0001504\n", "a[4] 0.396810887 0.73341977 -0.7484879 1.60863213 4610.8823 0.9996852\n", "a[5] -0.081867389 0.68455884 -1.1372001 1.03591740 5469.9431 1.0000679\n", "a[6] -0.073562695 0.71342897 -1.2177587 1.09017998 5130.5129 0.9995533\n", "a[7] 0.391493658 0.76835333 -0.7467720 1.67546422 4158.3462 0.9997849\n", "a[8] -0.077672429 0.71342739 -1.2207131 1.08462669 4612.9119 0.9993553\n", "a[9] -0.275556310 0.53007489 -1.1456814 0.56789648 4072.1194 0.9993842\n", "a[10] 1.083916853 0.59780561 0.1604030 2.07252886 3372.1984 0.9993962\n", "a[11] 0.515366726 0.55919568 -0.3630818 1.42150703 3304.4540 1.0008314\n", "a[12] 0.256253729 0.54397209 -0.6027094 1.10748121 3376.5464 1.0001392\n", "a[13] 0.507371149 0.54253780 -0.3383925 1.37422264 4165.1205 0.9994616\n", "a[14] -0.019154027 0.53076770 -0.8700474 0.83096797 3398.9324 1.0000889\n", "a[15] 1.084497824 0.59215692 0.1710215 2.09371321 3286.2663 1.0000800\n", "a[16] 1.083833289 0.60537079 0.1432592 2.10200025 3836.9189 1.0000499\n", "a[17] 0.311359990 0.62295500 -0.6315440 1.32062429 3987.2987 0.9993120\n", "a[18] -0.016406295 0.59236703 -0.9468339 0.94955229 4037.9169 0.9997998\n", "a[19] -0.325798059 0.57463583 -1.2267136 0.61010962 4114.0977 1.0001319\n", "a[20] 0.714880887 0.67672986 -0.3007139 1.84490729 4203.5601 0.9998058\n", "a[21] -0.031969435 0.59121056 -0.9530994 0.93914665 4234.7039 0.9992996\n", "a[22] -0.028834440 0.58703520 -0.9301436 0.94422696 3964.1567 0.9995044\n", "a[23] -0.041898444 0.59765311 -0.9853586 0.93718093 4209.5053 0.9993394\n", "a[24] -0.594958996 0.53980600 -1.4501513 0.27491654 3875.6886 0.9994484\n", "a[25] -0.922065489 0.43447970 -1.6310744 -0.24752504 2623.0503 0.9997568\n", "a[26] 0.040021306 0.41800846 -0.6349270 0.69762218 2431.4703 1.0006699\n", "a[27] -1.247234379 0.46782385 -2.0144778 -0.53216369 2516.0727 1.0004558\n", "a[28] -0.485287300 0.41851536 -1.1705819 0.17420454 2349.9120 1.0001383\n", "a[29] 0.047076151 0.42232253 -0.6337015 0.70075034 2247.7332 1.0000059\n", "a[30] 1.044254424 0.45618381 0.3344624 1.78213795 2637.6238 1.0000159\n", "a[31] -0.626126045 0.41941549 -1.2956179 0.04965493 1935.7106 1.0002374\n", "a[32] -0.353929282 0.42071794 -1.0243468 0.29269038 2126.4161 1.0031737\n", "a[33] 0.471450515 0.59385007 -0.4268991 1.43683414 5077.8028 0.9994915\n", "a[34] 0.169549989 0.57957901 -0.7313541 1.12555060 3302.1348 0.9997328\n", "a[35] 0.161643000 0.57092408 -0.7005694 1.10204382 3356.3200 0.9994369\n", "a[36] -0.348806228 0.51888966 -1.1750501 0.48017641 3660.0056 1.0004628\n", "a[37] -0.345350105 0.52735836 -1.1802968 0.51616336 3714.7200 0.9993824\n", "a[38] 0.845436525 0.66721207 -0.1544767 1.95980305 3939.9955 0.9998421\n", "a[39] 0.162843299 0.58118370 -0.7135465 1.13912173 3949.5421 0.9996835\n", "a[40] -0.094286545 0.53314844 -0.9099927 0.77195836 3965.9727 0.9995954\n", "a[41] -1.568018639 0.45229941 -2.3055081 -0.87131821 2517.4945 1.0004870\n", "a[42] -0.578110805 0.37654285 -1.1815079 0.01066022 2046.9753 1.0004631\n", "a[43] -0.472536643 0.37636857 -1.0735304 0.11987256 1900.8481 1.0012754\n", "a[44] -0.367927755 0.37617701 -0.9810108 0.22073088 1693.1895 1.0016356\n", "a[45] 0.427653043 0.37664412 -0.1665974 1.02235529 1770.0766 1.0015635\n", "a[46] -0.575108971 0.37146068 -1.1738507 0.01541667 1716.4397 1.0004397\n", "a[47] 1.533185496 0.44959493 0.8328447 2.28363795 2106.3792 1.0005826\n", "a[48] -0.076281000 0.37718528 -0.6926673 0.52807620 1714.3057 1.0005010\n", "a_bar 0.009485129 0.09955516 -0.1492049 0.16871382 1371.0897 1.0006038\n", "sigma 0.828621783 0.14446428 0.6129801 1.06819666 1609.1266 1.0012639\n", "bPredator[1] 2.638227839 0.26352128 2.2212575 3.06821355 1510.8586 1.0009788\n", "bPredator[2] 0.023562060 0.22059236 -0.3288387 0.37112341 737.4917 1.0041597" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(precis(m_rf_pred_orig, depth = 2), mimetypes=\"text/plain\")" ] }, { "cell_type": "markdown", "id": "19a01b82", "metadata": {}, "source": [ "As explained above, this model struggles to sample. We've managed to avoid the warnings and achieve\n", "decent mixing by tightening a prior:" ] }, { "cell_type": "code", "execution_count": 8, "id": "9e50c32f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[1] 2000\n", "[1] 1\n", "[1] 2000\n" ] }, { "data": { "image/png": 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w8AF3W93hxO1sGoFxs2wk+vzHZFsg8iVldX9+3b98wzz1y1atW4ceMAYNmyZUcf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\nVarEtWwcrZ4KUkSV+O+bz+2T0appFrRQm+eyvr6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gXVUD69kJhWmWCL2gIrP9k5hDkaM3/5kDD/4cgCCPmy0AACAASURBVNeOPiIuhwHC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\nV8/u/HNlIRPQKjxTnOEoSBok4FMYWz6MED0Ld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wdSNdhm/xs1XMnBt3pQ9rSzaTxbCiXFgFY07tqnY/SQbK9ywZArmQdGfDhnvTEAHi/O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\nYzpNG9rYDR2nElfc1SlT5XLS7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IucqD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\n2qRDauvnCfpFpP9NZuEwFNMIpbbGNYNyNWk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Ltb3QB0nmoCAq5LouhrASihsBKMUpqAJIn8VIuwD2dOWpcCjh/ST9MGLbRJbtFQUwoAwN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\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gAVFRVHjhzpu0ypUgbh5PZTAoBhww7F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MMDmD0/k3xNz61pssbADS7JSFg36nzETS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\nhbg2zju4n6jLU6UKRClKYnz08cbMz4UD8Io5TTqQUE9Vpw5Q0dav2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gXDdPWonaFprpMTRhSAFU0YH9YNf5ncS8G741cMaM1plWS9jAGg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\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CHhyJj9meCs9o4zCp0yok3Q0wkkPnOTkOe7bCV/ajkNVAghxIUGKoQQQsIUq45L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\n3BY6ehRHj8beFN2y01zfBQCyUlxSKUNMmhSj0f4xENe9rcQ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}, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_15_2.png" } }, "output_type": "display_data" } ], "source": [ "iplot(function() {\n", " traceplot(m_rf_pred_orig, pars=c(\"a[41]\", \"a[30]\", \"a_bar\", \"sigma\", \"bPredator[1]\", \"bPredator[2]\"))\n", "}, ar=2)\n", "iplot(function() {\n", " trankplot(m_rf_pred_orig, pars=c(\"a[41]\", \"a[30]\", \"a_bar\", \"sigma\", \"bPredator[1]\", \"bPredator[2]\"))\n", "}, ar=2)" ] }, { "cell_type": "markdown", "id": "640696b6", "metadata": {}, "source": [ "Why are we struggling to sample? To debug this, let's go back to the chapter on debugging MCMC, in\n", "particular section **9.5.4.** on non-identifiable parameters. If non-identifiable parameters are a\n", "cause of this symptom, what could we check for? Going even further back, to the end of section\n", "**6.1**, the author suggests checking whether the posterior has changed relative to the prior. This\n", "is a good question to ask regularly; which parameters are unchanged relative to their prior? The\n", "obvious parameter is $\\bar{\\alpha}$, which we already had to tweak. Let's change the $\\bar{\\alpha}$\n", "prior again and see if it remains unchanged in the posterior:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta_{pred[i]} \\\\\n", "\\alpha_j & \\sim Normal(\\bar{\\alpha}, \\sigma), j = 1..48 \\\\\n", "\\bar{\\alpha} & \\sim Normal(1.0, 0.1) \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta_j & \\sim Normal(0, 1.5), j = 1..2\n", "\\end{align}\n", "$$" ] }, { "cell_type": "code", "execution_count": 9, "id": "b3328c8e", "metadata": {}, "outputs": [ { "data": { "image/png": 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6gbwLx2ERwqIDgudHLDtsBt9FOGugHMuwwMwaEAggM4oMhHcwgO4IDg0ByCAzig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\nCvoGsHO7CA4FlAZHVuhia1vQfrTCW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6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\nzf4PlrDIeZHdPVgAAAAASUVORK5CYII=" }, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_17_0.png" } }, "output_type": "display_data" }, { "data": { "text/markdown": [ "Raw data (preceding plot):" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff Rhat4 \n", "a[1] 0.89209569 0.67477533 -0.16745233 2.0011115 4735.4615 0.9992439\n", "a[2] 1.39224094 0.73818963 0.25400126 2.6080315 3957.1503 1.0004964\n", "a[3] 0.10122305 0.66283664 -0.97613390 1.1653688 3418.7183 1.0000106\n", "a[4] 1.38871216 0.73452590 0.28161585 2.5953023 3785.4037 0.9994385\n", "a[5] 0.90554711 0.69830248 -0.16292157 2.0571965 4904.7154 0.9998165\n", "a[6] 0.90176640 0.69104425 -0.19062266 2.0195898 4457.3569 0.9994585\n", "a[7] 1.39936938 0.75992449 0.20574222 2.6583386 4249.0306 0.9996905\n", "a[8] 0.91059656 0.68309855 -0.18988412 2.0056462 4003.0761 1.0012390\n", "a[9] 0.73248137 0.52721299 -0.11813063 1.5496131 3425.8315 0.9995393\n", "a[10] 2.06301112 0.58356879 1.19447321 3.0422058 2793.8910 1.0005541\n", "a[11] 1.49963661 0.52484637 0.66308684 2.3571843 3926.1740 1.0020691\n", "a[12] 1.23113983 0.54391426 0.37062379 2.1014719 3627.1536 1.0003903\n", "a[13] 1.49939343 0.54482885 0.65913121 2.3839408 3168.7937 1.0006681\n", "a[14] 0.98772905 0.52333559 0.15660760 1.8276881 3324.1530 1.0015907\n", "a[15] 2.06758066 0.57084495 1.21328743 3.0248502 3365.5445 0.9997303\n", "a[16] 2.06976816 0.60316648 1.14447531 3.0806674 4120.2195 0.9999741\n", "a[17] 1.29229894 0.60917356 0.37290175 2.2960869 4007.8210 1.0002482\n", "a[18] 0.94007920 0.57718091 0.05406167 1.8824613 3926.6926 0.9997396\n", "a[19] 0.65752522 0.55403428 -0.17795545 1.5459452 3541.3975 1.0012304\n", "a[20] 1.69407162 0.67858631 0.67788785 2.8359920 3233.6798 1.0019009\n", "a[21] 0.95862978 0.58846189 0.01658356 1.9128141 3413.0634 1.0002383\n", "a[22] 0.93698425 0.56500639 0.05393344 1.8602302 4012.3578 1.0001226\n", "a[23] 0.96240309 0.58264693 0.06316729 1.8934749 4503.2347 1.0006012\n", "a[24] 0.39965050 0.53998463 -0.43439589 1.2812131 3192.9299 1.0001324\n", "a[25] 0.07621943 0.43948050 -0.63167357 0.7536801 2181.3490 1.0013726\n", "a[26] 1.03888573 0.41344545 0.36588081 1.6863169 2452.7963 1.0023155\n", "a[27] -0.24250659 0.47663660 -1.02658207 0.4852501 2222.4989 1.0006004\n", "a[28] 0.49973971 0.41881256 -0.17784275 1.1666101 2290.0176 1.0008810\n", "a[29] 1.03235316 0.40609705 0.36608494 1.6754619 2286.3186 1.0019069\n", "a[30] 2.02159219 0.42916485 1.36954429 2.7244621 2305.3258 1.0005783\n", "a[31] 0.36793186 0.42202497 -0.31798667 1.0220448 2154.6493 1.0015990\n", "a[32] 0.64086201 0.41060626 -0.03934122 1.3016825 1963.1853 1.0011168\n", "a[33] 1.46138803 0.59516254 0.52792464 2.4607093 4247.0558 1.0013806\n", "a[34] 1.14174442 0.56920314 0.26951677 2.0622307 3790.0600 1.0008938\n", "a[35] 1.16039851 0.57498749 0.28519144 2.1135609 3559.2976 1.0015933\n", "a[36] 0.63760672 0.51303529 -0.16677345 1.4736388 3106.9969 1.0003387\n", "a[37] 0.63900192 0.51835456 -0.16468426 1.4894591 3150.7196 1.0003524\n", "a[38] 1.82482034 0.63775234 0.85172586 2.8864206 3479.1211 1.0005003\n", "a[39] 1.15723400 0.57205560 0.28350920 2.0816031 3242.3819 1.0019410\n", "a[40] 0.87573768 0.53712506 0.03494396 1.7547448 3325.7247 1.0000819\n", "a[41] -0.55852738 0.45148673 -1.32444554 0.1297604 2039.5352 1.0010345\n", "a[42] 0.42040389 0.37351131 -0.18386648 0.9985524 1871.0674 1.0024993\n", "a[43] 0.52256157 0.37881219 -0.09506383 1.1170410 1639.8070 1.0015673\n", "a[44] 0.61999632 0.36585617 0.03341034 1.2006817 1709.6801 1.0023348\n", "a[45] 1.42271809 0.36963628 0.84366835 2.0282822 1999.1441 1.0009946\n", "a[46] 0.41424304 0.37841286 -0.19656934 1.0070465 1839.1323 1.0011048\n", "a[47] 2.51436060 0.45221636 1.83604601 3.2685320 2747.6259 1.0002937\n", "a[48] 0.91928048 0.35897769 0.33980370 1.4889490 1605.9322 1.0022225\n", "a_bar 1.00359144 0.09591719 0.84977652 1.1545523 1255.1540 1.0053490\n", "sigma 0.82101396 0.14649139 0.60758009 1.0741069 1396.0209 1.0006210\n", "bPredator[1] 1.66349494 0.26370106 1.25552431 2.0945184 1281.1362 1.0030336\n", "bPredator[2] -0.96300955 0.21888214 -1.29949688 -0.6091436 708.4835 1.0063713" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "m_rf_pred_shift <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank] + bPredator[Predator],\n", " a[tank] ~ dnorm(a_bar, sigma),\n", " a_bar ~ dnorm(1.0, 0.1),\n", " sigma ~ dexp(1),\n", " bPredator[Predator] ~ dnorm(0, 1.5)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE, iter=2000\n", ")\n", "\n", "iplot(function() {\n", " plot(precis(m_rf_pred_shift, depth=2), main='m_rf_pred_shift')\n", "}, ar=1.0)\n", "display_markdown(\"Raw data (preceding plot):\")\n", "display(precis(m_rf_pred_shift, depth = 2), mimetypes=\"text/plain\")" ] }, { "cell_type": "markdown", "id": "e0dcc2ee", "metadata": {}, "source": [ "The $\\bar{\\alpha}$ prior remains unchanged even after being shifted. Notice that the predator\n", "parameters are the ones that have responded (and unsuprisingly, all the `a` parameters). Previously\n", "the model had inferred a 'lack of predator' drastically helps survival and a predator has no effect\n", "on survival (treating a predator as the baseline). Now it has inferred a predator hurts chances of\n", "survival, and the lack of a predator doesn't help as much. That is, all these parameters only make\n", "sense relative to each other.\n", "\n", "To avoid this mess we could use an indicator variable:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta P_i \\\\\n", "\\alpha_j & \\sim Normal(\\bar{\\alpha}, \\sigma), j = 1..48 \\\\\n", "\\bar{\\alpha} & \\sim Normal(0, 2) \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta & \\sim Normal(0, 1.5)\n", "\\end{align}\n", "$$" ] }, { "cell_type": "code", "execution_count": 10, "id": "be2175c6", "metadata": {}, "outputs": [ { "data": { "image/png": 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4hDDSAOOjrdZpynrHV8I7sTH0McHXjJFOJQg8ASR/oyH/Ixe8c56dLKly+js13u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" }, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_19_0.png" } }, "output_type": "display_data" }, { "data": { "text/markdown": [ "Raw data (preceding plot):" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff Rhat4 \n", "a[1] 2.5522648 0.7005179 1.4704404 3.724137 6465.3677 0.9997779\n", "a[2] 3.0204002 0.7509938 1.8883086 4.273045 4801.7676 1.0000717\n", "a[3] 1.7453122 0.6243500 0.7505595 2.729144 5643.3185 0.9999198\n", "a[4] 3.0308241 0.7630791 1.8813480 4.323262 5013.6301 0.9998198\n", "a[5] 2.5490308 0.6825154 1.4863144 3.682729 5641.1540 1.0000314\n", "a[6] 2.5490481 0.6828359 1.4998263 3.666704 6223.8256 0.9999237\n", "a[7] 3.0277615 0.7447970 1.9050250 4.254546 4683.1569 0.9999306\n", "a[8] 2.5523347 0.6957374 1.4755051 3.710511 6337.5569 1.0006373\n", "a[9] 2.3564626 0.5704366 1.4249326 3.246933 2273.3989 0.9999730\n", "a[10] 3.6979365 0.6404354 2.7154496 4.759738 2307.2144 1.0012041\n", "a[11] 3.1357584 0.5848394 2.2227532 4.082508 2218.6606 1.0003584\n", "a[12] 2.8730044 0.5714784 1.9691444 3.807295 2342.4570 0.9998993\n", "a[13] 3.1333766 0.6008392 2.1954840 4.093771 2193.1768 1.0007692\n", "a[14] 2.6121693 0.5773987 1.6854409 3.532968 2250.0685 1.0006250\n", "a[15] 3.7063579 0.6486675 2.7129112 4.778418 2321.4588 1.0004578\n", "a[16] 3.6995097 0.6422066 2.7268487 4.771852 2525.4463 1.0000863\n", "a[17] 2.9315669 0.6131325 1.9981556 3.953931 5284.7219 0.9998453\n", "a[18] 2.6011891 0.5676435 1.7185426 3.537737 5644.0729 0.9998619\n", "a[19] 2.3008860 0.5254164 1.4853700 3.157238 6758.9622 1.0004038\n", "a[20] 3.3397761 0.6888784 2.3057830 4.505656 4574.8774 0.9996914\n", "a[21] 2.6044994 0.5763145 1.7208334 3.553111 5326.6637 1.0001091\n", "a[22] 2.5991773 0.5630963 1.7358827 3.526439 6609.4474 1.0001926\n", "a[23] 2.5974198 0.5701527 1.7355686 3.530736 6394.1215 0.9998074\n", "a[24] 2.0506006 0.5165176 1.2566012 2.894075 6907.7744 1.0001762\n", "a[25] 1.7243139 0.4917251 0.9252327 2.495221 1611.2019 1.0002243\n", "a[26] 2.6686296 0.4623173 1.9255557 3.409024 1480.8194 1.0003777\n", "a[27] 1.3971871 0.5191158 0.5484776 2.186560 1664.7034 1.0000776\n", "a[28] 2.1433253 0.4678318 1.3789682 2.885350 1538.8003 1.0004297\n", "a[29] 2.6707417 0.4714297 1.9044658 3.417621 1534.8110 1.0003517\n", "a[30] 3.6664625 0.5007730 2.8731590 4.493474 1466.1202 1.0003867\n", "a[31] 2.0054734 0.4709779 1.2607800 2.755354 1490.3879 1.0004900\n", "a[32] 2.2792674 0.4685247 1.5218700 3.025201 1588.9496 1.0003599\n", "a[33] 3.1158945 0.5974454 2.2051671 4.128562 5757.0877 0.9996544\n", "a[34] 2.8078013 0.5453006 1.9912577 3.721995 5840.2122 0.9999484\n", "a[35] 2.7949597 0.5440604 1.9722512 3.710830 5590.0865 1.0001520\n", "a[36] 2.2903009 0.4728252 1.5763166 3.079256 6214.4524 1.0000563\n", "a[37] 2.2948037 0.4790739 1.5722842 3.084986 6157.2150 0.9998679\n", "a[38] 3.4649569 0.6816790 2.4613353 4.617711 4279.8047 1.0000297\n", "a[39] 2.7880349 0.5380635 1.9720357 3.683688 5951.3460 0.9999877\n", "a[40] 2.5410647 0.5103372 1.7516598 3.399963 6211.9274 1.0000169\n", "a[41] 1.0668785 0.5055053 0.2238685 1.846239 1695.9204 1.0003529\n", "a[42] 2.0509100 0.4399465 1.3463682 2.753869 1367.0356 1.0003402\n", "a[43] 2.1523915 0.4452148 1.4372461 2.863473 1392.6392 1.0007920\n", "a[44] 2.2617789 0.4340331 1.5606782 2.940569 1261.3145 1.0007757\n", "a[45] 3.0598169 0.4385458 2.3552809 3.754512 1281.9748 1.0002635\n", "a[46] 2.0561885 0.4473343 1.3340787 2.775770 1360.7541 0.9999792\n", "a[47] 4.1475119 0.5009864 3.3612204 4.959540 1600.1446 1.0000179\n", "a[48] 2.5585814 0.4290491 1.8812055 3.243232 1297.0543 1.0004239\n", "a_bar 2.6418635 0.2431518 2.2643128 3.034041 887.3094 1.0005768\n", "sigma 0.8196008 0.1450572 0.6112842 1.064260 2140.9977 1.0006708\n", "bPredator -2.6028713 0.3128245 -3.0963048 -2.096804 731.0829 1.0009372" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rf_dat <- list(\n", " S = rf_df$surv,\n", " N = rf_df$density,\n", " tank = rf_df$tank,\n", " Predator = ifelse(rf_df$Predator == 1, 0, 1)\n", ")\n", "m_rf_pred_indicator <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank] + bPredator * Predator,\n", " a[tank] ~ dnorm(a_bar, sigma),\n", " a_bar ~ dnorm(0, 2),\n", " sigma ~ dexp(1),\n", " bPredator ~ dnorm(0, 3)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE, iter=4000\n", ")\n", "\n", "iplot(function() {\n", " plot(precis(m_rf_pred_indicator, depth=2), main='m_rf_pred_indicator')\n", "}, ar=1.0)\n", "display_markdown(\"Raw data (preceding plot):\")\n", "display(precis(m_rf_pred_indicator, depth = 2), mimetypes=\"text/plain\")" ] }, { "cell_type": "markdown", "id": "0484a2d9", "metadata": {}, "source": [ "Notice in the last model we've been able to widen the $\\bar{\\alpha}$ prior and actually learn it\n", "from the data, that is, the prior changes in the posterior.\n", "\n", "Still, an indicator variable isn't ideal for at least one of the reasons given in section\n", "**5.3.1.**: We aren't more uncertain about the predator than the non-predator situation. The\n", "indicator variable approach also makes it harder to read the `a` parameters relative to `a_bar`\n", "since they aren't centered at zero, and makes it harder to set an `a_bar` prior.\n", "\n", "Instead let's simply fix the `a_bar` prior's expected value to zero as suggested in section\n", "**13.3.1**:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta_{pred[i]} \\\\\n", "\\alpha_j & \\sim Normal(0, \\sigma), j = 1..48 \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta_j & \\sim Normal(0, 1.5), j = 1..2\n", "\\end{align}\n", "$$" ] }, { "cell_type": "code", "execution_count": 11, "id": "7745ca84", "metadata": {}, "outputs": [ { "data": { "image/png": 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cAkEIfKBCmOZoyxpNJXebVVG0yOqgwgDicBcagMeQLYvpF+b83eW5AAJj0Qh8pQ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}, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_21_0.png" } }, "output_type": "display_data" }, { "data": { "text/markdown": [ "Raw data (preceding plot):" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff Rhat4 \n", "a[1] -0.09697859 0.6841610 -1.1624090 0.978796500 7104.0967 0.9991372\n", "a[2] 0.39051532 0.7118729 -0.7055822 1.585237467 4997.2601 0.9997518\n", "a[3] -0.88904449 0.6238732 -1.8911480 0.087113890 4115.0420 0.9999485\n", "a[4] 0.41269873 0.7425609 -0.7262197 1.638435915 5028.8425 0.9994130\n", "a[5] -0.08992742 0.6658583 -1.1304364 0.979097793 4868.8726 1.0002809\n", "a[6] -0.10079296 0.6726996 -1.1429354 0.978045998 5619.5932 0.9998326\n", "a[7] 0.38246971 0.7259052 -0.7097182 1.584208094 4646.3051 0.9996028\n", "a[8] -0.07450817 0.6763312 -1.1585558 1.022350219 4882.5723 0.9998955\n", "a[9] -0.27823505 0.5226344 -1.1208755 0.547098083 3865.5537 0.9999979\n", "a[10] 1.07936183 0.5812063 0.1974903 2.007386701 4001.4846 1.0009419\n", "a[11] 0.49797296 0.5371057 -0.3283804 1.358467547 4659.2236 1.0001918\n", "a[12] 0.23363445 0.5416713 -0.6148350 1.113431663 4300.4459 0.9995509\n", "a[13] 0.51324613 0.5455704 -0.3571918 1.401333472 4995.6051 0.9994275\n", "a[14] -0.01964218 0.5098752 -0.8471211 0.767138747 3755.1251 1.0003357\n", "a[15] 1.07173121 0.5855436 0.1844398 2.030393592 4504.2158 0.9999240\n", "a[16] 1.07566945 0.5792244 0.1801974 2.023543821 4490.1072 0.9998481\n", "a[17] 0.29275396 0.6396542 -0.6886191 1.391203496 5798.8060 0.9993214\n", "a[18] -0.04523565 0.5757471 -0.9454994 0.938394996 5220.0649 0.9993111\n", "a[19] -0.32044369 0.5471879 -1.1695065 0.552227484 3969.2413 1.0002053\n", "a[20] 0.67529437 0.6791460 -0.3326967 1.833778951 4212.5325 0.9996342\n", "a[21] -0.03522830 0.5792738 -0.9324501 0.908435970 4574.5422 0.9994619\n", "a[22] -0.03968798 0.5670331 -0.8942994 0.897039310 4903.4849 0.9994307\n", "a[23] -0.03165309 0.5728453 -0.9131142 0.901236994 4867.8231 1.0000564\n", "a[24] -0.59880483 0.5256781 -1.4429958 0.226346990 4048.9714 0.9991929\n", "a[25] -0.92613069 0.4258198 -1.6141886 -0.264702371 3117.3589 0.9995583\n", "a[26] 0.03769847 0.4021599 -0.6019276 0.677847891 3170.7403 1.0012505\n", "a[27] -1.23936592 0.4522377 -1.9862324 -0.544366300 2848.3630 1.0003908\n", "a[28] -0.49235389 0.4134558 -1.1593876 0.167492659 2823.6535 1.0003123\n", "a[29] 0.04646079 0.3889926 -0.5785333 0.664016953 2624.6351 1.0015064\n", "a[30] 1.03414342 0.4395880 0.3480782 1.765167828 3529.6936 1.0000845\n", "a[31] -0.62693058 0.4122822 -1.2835615 0.008595614 3179.6959 0.9996412\n", "a[32] -0.35547092 0.4005949 -1.0154093 0.274143421 2859.0685 1.0014165\n", "a[33] 0.48630083 0.6185443 -0.4274168 1.521135912 4609.1703 0.9993187\n", "a[34] 0.16418432 0.5472980 -0.6807129 1.085121870 5050.9348 0.9993816\n", "a[35] 0.17030285 0.5570812 -0.6707985 1.076228321 3845.2128 0.9999526\n", "a[36] -0.34515564 0.5115704 -1.1373833 0.476882477 3764.8778 0.9996538\n", "a[37] -0.34532324 0.5059938 -1.1250993 0.480615388 4662.9715 0.9994801\n", "a[38] 0.83753669 0.6862194 -0.1984012 1.975697764 5109.4183 0.9995974\n", "a[39] 0.15282231 0.5640697 -0.7004958 1.092202698 5035.6147 0.9997246\n", "a[40] -0.11355840 0.5107425 -0.9154867 0.726645541 3879.4945 0.9996644\n", "a[41] -1.56458436 0.4502418 -2.3268471 -0.883605386 2629.1010 1.0007711\n", "a[42] -0.58326697 0.3730827 -1.1916108 0.011371234 2902.3533 1.0006533\n", "a[43] -0.47753634 0.3612391 -1.0614049 0.091031124 2393.1816 1.0008698\n", "a[44] -0.37480105 0.3587195 -0.9656114 0.188737115 2328.3670 1.0013135\n", "a[45] 0.42094747 0.3676015 -0.1570650 1.010639836 2734.5974 1.0007342\n", "a[46] -0.58616032 0.3700466 -1.1823389 -0.006083808 2481.4581 1.0027914\n", "a[47] 1.52162086 0.4242206 0.8779488 2.224791652 2704.3370 1.0003412\n", "a[48] -0.07801268 0.3640619 -0.6608928 0.501107049 2658.8869 1.0022556\n", "sigma 0.82165527 0.1394925 0.6132546 1.062145001 1399.6148 1.0003748\n", "bPredator[1] 2.64280559 0.2451182 2.2609478 3.040105815 2013.0146 1.0001101\n", "bPredator[2] 0.03032788 0.1982585 -0.2796168 0.349500599 963.9921 1.0028167" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rf_dat <- list(\n", " S = rf_df$surv,\n", " N = rf_df$density,\n", " tank = rf_df$tank,\n", " Predator = rf_df$Predator\n", ")\n", "m_rf_df_pred <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank] + bPredator[Predator],\n", " a[tank] ~ dnorm(0, sigma),\n", " sigma ~ dexp(1),\n", " bPredator[Predator] ~ dnorm(0, 1.5)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE, iter=2000\n", ")\n", "\n", "iplot(function() {\n", " plot(precis(m_rf_df_pred, depth=2), main='m_rf_df_pred')\n", "}, ar=1.0)\n", "display_markdown(\"Raw data (preceding plot):\")\n", "display(precis(m_rf_df_pred, depth = 2), mimetypes=\"text/plain\")" ] }, { "cell_type": "markdown", "id": "2ad35cfc", "metadata": {}, "source": [ "Let's fit a similar model with only the `size` predictor:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta_{size[i]} \\\\\n", "\\alpha_j & \\sim Normal(0, \\sigma), j = 1..48 \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta_j & \\sim Normal(0, 1.5), j = 1..2\n", "\\end{align}\n", "$$" ] }, { "cell_type": "code", "execution_count": 12, "id": "0113f816", "metadata": {}, "outputs": [ { "data": { "image/png": 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IE6OvATXSfFQBx2ZNvTgwZMzQropRAHH6ijA+uKe8cZHII42AFx8IE6OvD0R2tb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}, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_23_0.png" } }, "output_type": "display_data" }, { "data": { "text/markdown": [ "Raw data (preceding plot):" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff Rhat4 \n", "a[1] 0.97752303 0.8835042 -0.32453635 2.46154161 2430.2235 1.0012180\n", "a[2] 1.86327598 1.0624751 0.30664617 3.65467852 2537.9613 1.0017688\n", "a[3] -0.10443315 0.7230797 -1.21230383 1.06307623 1940.0259 1.0016095\n", "a[4] 1.87033162 1.0752683 0.27684865 3.71942342 2934.6080 1.0008884\n", "a[5] 0.65949438 0.9296719 -0.76855059 2.22705412 3080.9694 1.0011339\n", "a[6] 0.63542458 0.9206881 -0.73879582 2.14077619 2739.0607 1.0008519\n", "a[7] 1.61518718 1.1494012 -0.05417674 3.53659232 2273.5358 0.9993930\n", "a[8] 0.66273450 0.9182667 -0.70231129 2.23267394 2338.0138 0.9999125\n", "a[9] -1.28242464 0.6779740 -2.36918377 -0.22965485 1702.2136 1.0005464\n", "a[10] 0.98409873 0.8912791 -0.36259458 2.46901686 2614.4988 1.0006619\n", "a[11] -0.11020205 0.7321976 -1.23599653 1.10713271 1925.7231 0.9999628\n", "a[12] -0.52380795 0.6829459 -1.60787257 0.57698456 1771.8878 1.0003157\n", "a[13] -0.49610098 0.7443987 -1.63784388 0.68404612 2191.9232 1.0010597\n", "a[14] -1.32474819 0.6885549 -2.42596473 -0.21554533 2186.7153 1.0004160\n", "a[15] 0.65758409 0.9284452 -0.71527759 2.18234668 2422.1029 1.0016655\n", "a[16] 0.64374669 0.9124251 -0.70765879 2.18761902 3129.5615 0.9996408\n", "a[17] 1.76336221 0.7885090 0.55543932 3.06380870 2786.8698 1.0004905\n", "a[18] 1.28464199 0.7152119 0.19101763 2.45304314 1785.5785 1.0010351\n", "a[19] 0.91279649 0.6460401 -0.06653632 1.99398924 1845.2972 1.0016696\n", "a[20] 2.48738601 0.9936424 1.07549218 4.20363364 2617.9282 1.0002907\n", "a[21] 0.88984898 0.7341968 -0.22559476 2.10225237 2080.4659 1.0006731\n", "a[22] 0.88460185 0.7577859 -0.26811851 2.13897933 2145.1575 1.0012040\n", "a[23] 0.86302654 0.7224245 -0.21699469 2.09702860 2403.2826 0.9997079\n", "a[24] 0.17477428 0.6210206 -0.77787076 1.19973949 1740.9190 1.0032064\n", "a[25] -2.09351668 0.5443075 -2.99248210 -1.25033531 1301.0796 1.0017277\n", "a[26] -0.92071091 0.5170888 -1.73999848 -0.08758907 1263.7412 1.0032009\n", "a[27] -2.51160448 0.5779779 -3.49405576 -1.64633955 1390.5255 1.0008773\n", "a[28] -1.54911141 0.5304216 -2.41313158 -0.71722523 1208.2725 1.0005355\n", "a[29] -1.38780572 0.5150797 -2.22767237 -0.58240377 1330.5323 1.0026714\n", "a[30] -0.08334482 0.5934668 -1.01964309 0.85913071 1612.7431 1.0036123\n", "a[31] -2.17321305 0.5413917 -3.05741826 -1.33792005 1342.1802 1.0034081\n", "a[32] -1.84227386 0.5343419 -2.73825437 -1.00906277 1359.2655 1.0035962\n", "a[33] 2.05994892 0.7798711 0.90032973 3.37892869 2370.3716 1.0000161\n", "a[34] 1.58991185 0.6802528 0.55802614 2.68983709 1817.1788 1.0005279\n", "a[35] 1.59839736 0.7014364 0.52523148 2.77829088 1607.0835 1.0036347\n", "a[36] 0.95641017 0.5890629 0.01526481 1.89197674 1390.8940 1.0016272\n", "a[37] 0.52103424 0.6031463 -0.42626574 1.51350427 1768.2851 1.0017421\n", "a[38] 2.42872363 1.0374497 0.92145929 4.21005058 2299.1514 1.0003496\n", "a[39] 1.18261013 0.7147161 0.09191460 2.36356186 2141.0947 1.0009511\n", "a[40] 0.82536880 0.6248690 -0.14496913 1.85081628 1862.9680 1.0021163\n", "a[41] -2.89293403 0.5725528 -3.86403288 -2.01178169 1118.2075 1.0033815\n", "a[42] -1.65419161 0.4853054 -2.44458463 -0.88896203 1000.3817 1.0016024\n", "a[43] -1.53368467 0.4764261 -2.31780764 -0.78687128 993.8615 1.0009041\n", "a[44] -1.42242505 0.4768055 -2.20032668 -0.67186286 938.4543 1.0017574\n", "a[45] -0.95806009 0.4853153 -1.73491533 -0.19815837 1215.9525 1.0042005\n", "a[46] -2.11021208 0.4902764 -2.89647469 -1.32872259 1244.7923 1.0033629\n", "a[47] 0.52311701 0.5904331 -0.40693924 1.48374522 1567.3817 1.0021215\n", "a[48] -1.53744448 0.4682381 -2.31937713 -0.79495099 1164.7406 1.0030632\n", "sigma 1.61312478 0.2142123 1.30124065 1.98828592 1740.8490 1.0025179\n", "bSize[1] 1.06931649 0.3442443 0.53816609 1.62691389 577.5558 1.0049769\n", "bSize[2] 1.55123496 0.3528192 0.99305972 2.12098783 733.4177 1.0064655" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rf_dat <- list(\n", " S = rf_df$surv,\n", " N = rf_df$density,\n", " tank = rf_df$tank,\n", " Size = rf_df$Size\n", ")\n", "m_rf_df_size <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank] + bSize[Size],\n", " a[tank] ~ dnorm(0, sigma),\n", " sigma ~ dexp(1),\n", " bSize[Size] ~ dnorm(0, 1.5)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE, iter=2000\n", ")\n", "\n", "iplot(function() {\n", " plot(precis(m_rf_df_size, depth=2), main='m_rf_df_size')\n", "}, ar=1.0)\n", "display_markdown(\"Raw data (preceding plot):\")\n", "display(precis(m_rf_df_size, depth = 2), mimetypes=\"text/plain\")" ] }, { "cell_type": "markdown", "id": "05ea1ba2", "metadata": {}, "source": [ "Finally, lets model an interaction term. We've already added a 'treatment' index variable in\n", "preprocessing; see the data.frame near the start of this question.\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} + \\beta_{Treatment[i]} \\\\\n", "\\alpha_j & \\sim Normal(0, \\sigma), j = 1..48 \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\beta_j & \\sim Normal(0, 1.5), j = 1..4\n", "\\end{align}\n", "$$" ] }, { "cell_type": "code", "execution_count": 13, "id": "ef4ddedc", "metadata": {}, "outputs": [ { "data": { "image/png": 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z+y916h8qiLfEy7CA712P7O0bzvXp6yMMvmO4XKoy7yMXf6IDiUg99VATHo4wAT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\n+AzhAACfIRwA4LP/A/p0vl7So4+jAAAAAElFTkSuQmCC" }, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_25_0.png" } }, "output_type": "display_data" }, { "data": { "text/markdown": [ "Raw data (preceding plot):" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff \n", "a[1] -0.087257569 0.6477772 -1.11234636 0.93996928 4722.5288\n", "a[2] 0.318245478 0.6745471 -0.71460359 1.45023200 4778.9117\n", "a[3] -0.800963795 0.6008024 -1.77561418 0.13641758 3342.8367\n", "a[4] 0.302265247 0.6518208 -0.69100984 1.40382139 3496.4853\n", "a[5] -0.035445130 0.6249678 -1.03410501 0.96793664 5036.8068\n", "a[6] -0.032250608 0.6139588 -1.01072576 0.97492396 5164.0431\n", "a[7] 0.354867448 0.6353728 -0.61346231 1.40583923 4210.0953\n", "a[8] -0.043945496 0.6151364 -0.98306911 0.95695367 4749.5379\n", "a[9] 0.001957609 0.5208627 -0.83548335 0.82989428 4419.5517\n", "a[10] 1.196095698 0.5760802 0.33357862 2.14055378 3114.5423\n", "a[11] 0.704742593 0.5152675 -0.09071266 1.55676304 2997.9738\n", "a[12] 0.481584350 0.5021899 -0.29572659 1.29737687 4194.2670\n", "a[13] 0.221965804 0.5138389 -0.58784720 1.05716499 3667.6201\n", "a[14] -0.261465503 0.5124471 -1.10106069 0.53187012 3899.2559\n", "a[15] 0.736553286 0.5634339 -0.12468992 1.68514887 3311.3946\n", "a[16] 0.745341820 0.5492434 -0.07720214 1.67428163 4345.1706\n", "a[17] 0.251020002 0.5774214 -0.63275481 1.20814775 4588.8592\n", "a[18] -0.051935338 0.5627769 -0.94764556 0.85892117 3756.3156\n", "a[19] -0.318002893 0.5417412 -1.17314038 0.54672294 3210.6201\n", "a[20] 0.604834487 0.6319848 -0.34227492 1.66173991 3385.2257\n", "a[21] 0.033472764 0.5333835 -0.79554130 0.90861101 4043.5704\n", "a[22] 0.029242947 0.5428392 -0.82458011 0.91021538 4415.5132\n", "a[23] 0.034957911 0.5529902 -0.81975311 0.93719528 3632.9530\n", "a[24] -0.470096905 0.5063614 -1.28365869 0.33271814 3927.2373\n", "a[25] -0.517670247 0.4253073 -1.22039146 0.14365757 2979.9141\n", "a[26] 0.395552981 0.4141425 -0.25771856 1.07265705 3025.9498\n", "a[27] -0.843342418 0.4681718 -1.60698350 -0.12182338 2667.5470\n", "a[28] -0.114857926 0.4223913 -0.80308511 0.54755944 2796.1127\n", "a[29] -0.282946147 0.3973980 -0.91493729 0.35204248 2595.8095\n", "a[30] 0.663597991 0.4361002 -0.02320321 1.37190893 2954.9465\n", "a[31] -0.907729257 0.4230211 -1.57233709 -0.24741158 1978.1305\n", "a[32] -0.658813684 0.4163325 -1.34268637 -0.01756846 2263.8078\n", "a[33] 0.401378759 0.5762771 -0.47515903 1.35544512 4357.1064\n", "a[34] 0.136819073 0.5360838 -0.70850460 1.01958949 4029.9205\n", "a[35] 0.133440081 0.5397772 -0.68993194 1.05455481 4238.6507\n", "a[36] -0.326567524 0.4924184 -1.08865937 0.46026124 4043.2871\n", "a[37] -0.236285314 0.4737229 -0.99774743 0.51750538 3483.7743\n", "a[38] 0.787539951 0.6079236 -0.12172403 1.81772432 2932.5664\n", "a[39] 0.218542419 0.5309329 -0.59404407 1.08255773 4175.5458\n", "a[40] -0.020655554 0.5090984 -0.82681174 0.80482873 3577.4556\n", "a[41] -1.129685951 0.4485302 -1.87230867 -0.42836194 2292.7948\n", "a[42] -0.178347382 0.3754678 -0.79923448 0.40450969 2828.1548\n", "a[43] -0.071638312 0.3756510 -0.66980700 0.52025454 2681.6744\n", "a[44] 0.019679012 0.3738944 -0.58021129 0.61633966 2643.5542\n", "a[45] 0.065156173 0.3699510 -0.53374719 0.65132274 2468.8254\n", "a[46] -0.899000138 0.3933015 -1.51634559 -0.27886996 2164.0248\n", "a[47] 1.114395643 0.4469646 0.42623423 1.82967537 2565.2845\n", "a[48] -0.415071015 0.3848530 -1.04290846 0.18833472 2107.4585\n", "sigma 0.735941763 0.1459044 0.51628227 0.98159040 981.8263\n", "bTreatment[1] 2.661419274 0.3253302 2.15441259 3.18572489 2589.9114\n", "bTreatment[2] -0.443829846 0.2563421 -0.84018144 -0.02537645 1483.9414\n", "bTreatment[3] 2.497303072 0.3161132 2.00347641 2.99792231 2213.3737\n", "bTreatment[4] 0.460283400 0.2527771 0.05946582 0.86930412 1310.9256\n", " Rhat4 \n", "a[1] 1.0020151\n", "a[2] 1.0006531\n", "a[3] 1.0013384\n", "a[4] 1.0000362\n", "a[5] 0.9997723\n", "a[6] 0.9995127\n", "a[7] 1.0003023\n", "a[8] 0.9994760\n", "a[9] 0.9994705\n", "a[10] 0.9997850\n", "a[11] 1.0004945\n", "a[12] 1.0000306\n", "a[13] 0.9996838\n", "a[14] 0.9999756\n", "a[15] 1.0002805\n", "a[16] 0.9994730\n", "a[17] 0.9994418\n", "a[18] 0.9995753\n", "a[19] 1.0000075\n", "a[20] 1.0006909\n", "a[21] 0.9999656\n", "a[22] 0.9997511\n", "a[23] 0.9999732\n", "a[24] 0.9997563\n", "a[25] 1.0000648\n", "a[26] 1.0000309\n", "a[27] 1.0003747\n", "a[28] 1.0000041\n", "a[29] 0.9994521\n", "a[30] 1.0001314\n", "a[31] 1.0004173\n", "a[32] 0.9999176\n", "a[33] 0.9995793\n", "a[34] 0.9996435\n", "a[35] 0.9996489\n", "a[36] 0.9995608\n", "a[37] 1.0000851\n", "a[38] 1.0009833\n", "a[39] 0.9997947\n", "a[40] 0.9998519\n", "a[41] 1.0006167\n", "a[42] 1.0006921\n", "a[43] 0.9997063\n", "a[44] 1.0003002\n", "a[45] 0.9992996\n", "a[46] 1.0000655\n", "a[47] 1.0003963\n", "a[48] 1.0008080\n", "sigma 1.0046172\n", "bTreatment[1] 1.0005507\n", "bTreatment[2] 1.0007625\n", "bTreatment[3] 1.0000693\n", "bTreatment[4] 1.0008946" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rf_dat <- list(\n", " S = rf_df$surv,\n", " N = rf_df$density,\n", " tank = rf_df$tank,\n", " Treatment = rf_df$Treatment\n", ")\n", "m_rf_df_interaction <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank] + bTreatment[Treatment],\n", " a[tank] ~ dnorm(0, sigma),\n", " sigma ~ dexp(1),\n", " bTreatment[Treatment] ~ dnorm(0, 1.5)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE, iter=2000\n", ")\n", "\n", "iplot(function() {\n", " plot(precis(m_rf_df_interaction, depth=2), main='m_rf_df_interaction')\n", "}, ar=1.0)\n", "display_markdown(\"Raw data (preceding plot):\")\n", "display(precis(m_rf_df_interaction, depth = 2), mimetypes=\"text/plain\")" ] }, { "cell_type": "markdown", "id": "1d5c7077", "metadata": {}, "source": [ "Let's go back to the original question:\n", "\n", "> Instead of focusing on inferences about these two predictor variables, focus on the inferred\n", "> variation across tanks. Explain why it changes as it does across models.\n", "\n", "The inferred variation across tanks ($\\sigma$) decreases in these models as we add more predictors.\n", "We see the largest $\\sigma$ in `m13.2` where we haven't tried to explain variation with any\n", "predictors. When we add the predator predictor in `m_rf_df_pred` we see `sigma` drop significantly\n", "because there is a lot of predictive power in that variable (or at least more than `size`). The\n", "model with an interaction term has the lowest inference for `sigma` because it indirectly has access\n", "to all the predictors.\n", "\n", "One question only exists in **13H4**:\n", "\n", "> What do you infer about the causal inference of these predictor variables?\n", "\n", "In the typical predator-prey relationship it's more appropriate to use differential equations to\n", "model the relationship between the populations. Reading the original paper, though, it appears that\n", "the presence of predators, tadpole sizes, and initial density were manipulated. If that is the case\n", "then the causal diagram would be relatively simple: the predictors can only affect the outcome, not\n", "each other.\n", "\n", "It's tempting to read from the difference between `bTreatment[1]` and `bTreatment[3]` relative to\n", "the difference between `bTreatment[2]` and `bTreatment[4]` that being large helps survival in the\n", "absence of predators (to overcome the elements/nature) but in the presence of predators being large\n", "makes a tadpole easier to catch (harder to hide) and more desirable to catch.\n", "\n", "The support for the advantage of size in the absence of predators is limited, though, considering\n", "the error bars on `bTreatment[1]` and `bTreatment[3]`. If we only accept the significant difference\n", "in survivability from being smaller in the presence of predators, we would conclude being small\n", "would primarily be an advantage in the larval/tadpole stage of the frog's development without an\n", "explanation for why some tadpoles hatch larger. Based on the original paper, the confounding\n", "variable seems to be survivability at metamorphosis, which could influence the timing of hatching\n", "and therefore the ideal tadpole size. Tadpoles that are smaller at metamorphosis may be less likely\n", "to survive (or reproduce) than those that are larger.\n", "\n", "That is, there are two influences on the ideal tadpole size, both survivability at life stages in\n", "nature:\n", "```\n", "MetaSurv -> TadpoleSize <- LarvSurv\n", "```\n", "\n", "The species (apparently) has to tradeoff size to survive both stages.\n", "\n", "**13M2.** Compare the models you fit just above, using WAIC. Can you reconcile the differences in\n", "WAIC with the posterior distributions of the models?\n", "\n", "**Answer.** For comparison and to check on warnings, these results include `PSIS` deviances as well.\n", "Notice the model with the predator predictor does well in both comparisons. This predictor\n", "significantly improves predictive accuracy at the cost of only one parameter. Generally speaking the\n", "model with only the size predictor does not do as well, because (alone) this is not an effective\n", "predictor of whether the tadpole will survive to metamorphosis.\n", "\n", "In general there are not large differences between these models, however, considering the error bars\n", "produced by both WAIC and PSIS." ] }, { "cell_type": "code", "execution_count": 14, "id": "eb2bacaa", "metadata": {}, "outputs": [ { "data": { "image/png": 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3mGkilXmrahEA7l5tD6ph1dbdT2Xcb20WPynim0XvRQ3PkY/l+viYba06hDTsGO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\nAKj2/xhuBR/Hb2lcAAAAAElFTkSuQmCC" }, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_27_0.png" } }, "output_type": "display_data" }, { "data": { "text/markdown": [ "Raw data (preceding plot):" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ " WAIC SE dWAIC dSE pWAIC weight \n", "m13.2 199.0271 7.317398 0.0000000 NA 20.52833 0.4163127\n", "m_rf_df_pred 199.9161 9.232676 0.8890021 5.761711 19.59478 0.2669165\n", "m_rf_df_size 200.9270 7.066293 1.8998788 1.016211 21.21073 0.1610150\n", "m_rf_df_interaction 200.9934 9.684257 1.9662939 6.970610 19.53916 0.1557559" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "Some Pareto k values are very high (>1). Set pointwise=TRUE to inspect individual points.\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Some Pareto k values are very high (>1). Set pointwise=TRUE to inspect individual points.\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Some Pareto k values are very high (>1). Set pointwise=TRUE to inspect individual points.\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Some Pareto k values are very high (>1). Set pointwise=TRUE to inspect individual points.\n", "\n" ] }, { "data": { "image/png": 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}, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_27_7.png" } }, "output_type": "display_data" }, { "data": { "text/markdown": [ "Raw data (preceding plot):" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ " PSIS SE dPSIS dSE pPSIS weight \n", "m_rf_df_interaction 215.4582 12.018328 0.0000000 NA 26.77156 0.376661627\n", "m13.2 215.7296 8.498153 0.2713941 9.115141 28.87958 0.328865935\n", "m_rf_df_pred 215.9888 11.378194 0.5306113 4.814114 27.63113 0.288888725\n", "m_rf_df_size 223.8812 7.984385 8.4229865 9.625212 32.68783 0.005583713" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "iplot(function() {\n", " plot(compare(m13.2, m_rf_df_pred, m_rf_df_size, m_rf_df_interaction))\n", "}, ar=3.5)\n", "display_markdown(\"Raw data (preceding plot):\")\n", "display(compare(m13.2, m_rf_df_pred, m_rf_df_size, m_rf_df_interaction), mimetypes=\"text/plain\")\n", "\n", "p_comp = compare(m13.2, m_rf_df_pred, m_rf_df_size, m_rf_df_interaction, func=PSIS)\n", "iplot(function() {\n", " plot(p_comp)\n", "}, ar=3.5)\n", "display_markdown(\"Raw data (preceding plot):\")\n", "display(p_comp, mimetypes=\"text/plain\")" ] }, { "cell_type": "markdown", "id": "12f2df83", "metadata": {}, "source": [ "**13M3.** Re-estimate the basic Reed frog varying intercept model, but now using a Cauchy\n", "distribution in place of the Gaussian distribution for the varying intercepts. That is, fit this\n", "model:\n", "\n", "$$\n", "\\begin{align}\n", "S_i & \\sim Binomial(N_i,p_i) \\\\\n", "logit(p_i) & = \\alpha_{tank[i]} \\\\\n", "\\alpha_{tank} & \\sim Cauchy(\\alpha, \\sigma), tank = 1..48 \\\\\n", "\\alpha & \\sim Normal(0, 1) \\\\\n", "\\sigma & \\sim Exponential(1) \\\\\n", "\\end{align}\n", "$$\n", "\n", "(You are likely to see many divergent transitions for this model. Can you figure out why? Can you\n", "fix them?) Compare the posterior means of the intercepts, $\\alpha_{tank}$, to the posterior means\n", "produced in the chapter, using the customary Gaussian prior. Can you explain the pattern of\n", "differences? Take note of any change in the mean $\\alpha$ as well.\n", "\n", "**Answer.** First, let's reproduce some of the plots from the chapter. Similar to the approach in\n", "the `R code 13.22` box and elsewhere, we'll print the raw output of `precis` for a model before its\n", "plots:\n", "\n", "[com1]: under_score" ] }, { "cell_type": "code", "execution_count": 15, "id": "e69a2033", "metadata": {}, "outputs": [ { "data": { "text/plain": [ " mean sd 5.5% 94.5% n_eff Rhat4 \n", "a[1] 2.166532834 0.8415777 0.94352287 3.5504316180 2487.705 0.9994595\n", "a[2] 3.083820555 1.1286709 1.46455255 5.0701086864 2743.009 1.0004070\n", "a[3] 1.016293639 0.6985934 -0.04076748 2.2287308266 3758.880 0.9991277\n", "a[4] 3.043958298 1.0851385 1.49588614 4.9413883041 2912.386 0.9998120\n", "a[5] 2.139423360 0.8904333 0.84651899 3.6387978108 3858.914 0.9997494\n", "a[6] 2.106234009 0.8548032 0.83426377 3.5369092492 4052.181 0.9988760\n", "a[7] 3.074045734 1.0832856 1.43759964 4.9418012232 2633.082 0.9996423\n", "a[8] 2.155537339 0.8840924 0.86141276 3.6540940431 2528.486 0.9995637\n", "a[9] -0.183009287 0.6181161 -1.18128721 0.7753945948 4670.277 0.9984721\n", "a[10] 2.155175584 0.8775133 0.86118519 3.6029886441 2723.008 0.9996099\n", "a[11] 1.016263791 0.7156066 -0.07593707 2.2010431997 4537.656 0.9989630\n", "a[12] 0.586259955 0.6082589 -0.35700958 1.5598335369 2945.767 0.9991685\n", "a[13] 0.993370216 0.6616831 0.02932024 2.0340490072 3422.754 0.9988980\n", "a[14] 0.200205841 0.5954573 -0.74466849 1.1526114496 6168.260 0.9985134\n", "a[15] 2.160777602 0.8852034 0.89140831 3.7249424638 2769.060 0.9984947\n", "a[16] 2.135269447 0.8728510 0.82302708 3.5372001103 3466.436 0.9996513\n", "a[17] 2.920866171 0.8218896 1.73692434 4.3532783713 3032.486 0.9983675\n", "a[18] 2.389906265 0.6457832 1.45755634 3.5092229445 3162.778 0.9996631\n", "a[19] 2.012956911 0.5895563 1.11296558 2.9988914401 3153.116 0.9986043\n", "a[20] 3.663996701 0.9911659 2.27516564 5.3380689361 2711.051 1.0013611\n", "a[21] 2.395792576 0.6640905 1.42501176 3.5243121341 2953.745 0.9988757\n", "a[22] 2.414117363 0.6710001 1.41611035 3.5427246122 2902.783 0.9986059\n", "a[23] 2.407671181 0.6921338 1.41916362 3.5353627632 2459.663 0.9989985\n", "a[24] 1.704750052 0.5293150 0.90629218 2.5495097822 3651.669 0.9988592\n", "a[25] -0.994319675 0.4532927 -1.75235510 -0.2927055601 4017.570 0.9988534\n", "a[26] 0.164556033 0.3937696 -0.45773453 0.8249454460 4677.469 0.9990814\n", "a[27] -1.428287992 0.4943052 -2.24252972 -0.7033488354 3889.606 0.9990090\n", "a[28] -0.473645576 0.4181870 -1.14362004 0.1987316685 4193.475 0.9988749\n", "a[29] 0.152870077 0.3892231 -0.45690627 0.7788458084 5067.647 0.9987500\n", "a[30] 1.448648952 0.4836664 0.69532944 2.2347934380 4506.236 0.9990361\n", "a[31] -0.645829116 0.4135679 -1.31555328 0.0006253300 4252.301 0.9999317\n", "a[32] -0.298607182 0.3836891 -0.92584145 0.2988842719 4034.821 0.9992044\n", "a[33] 3.168398158 0.7186510 2.10514401 4.3791047937 2653.573 1.0008589\n", "a[34] 2.716821745 0.6388658 1.74062328 3.7972089794 3392.903 0.9988065\n", "a[35] 2.697692077 0.6373798 1.76997299 3.7864685410 3245.377 0.9994348\n", "a[36] 2.071199176 0.5233694 1.31121377 2.9624441747 3371.962 1.0006748\n", "a[37] 2.060716382 0.5081973 1.29818835 2.9219161746 3209.431 0.9985773\n", "a[38] 3.911450602 1.0091420 2.47520448 5.6659437217 2368.681 1.0009199\n", "a[39] 2.721275412 0.6679960 1.72508201 3.8795193702 2366.981 0.9999171\n", "a[40] 2.335837792 0.5590744 1.48314458 3.2869636774 3345.704 0.9987150\n", "a[41] -1.792990832 0.4670499 -2.56949264 -1.0765227758 3350.595 0.9991847\n", "a[42] -0.574124729 0.3529837 -1.14964530 -0.0288867842 5625.134 0.9986725\n", "a[43] -0.452584154 0.3316090 -0.98495100 0.0796395604 3678.316 0.9994217\n", "a[44] -0.337160405 0.3427056 -0.89481695 0.2156299349 3397.883 0.9987282\n", "a[45] 0.578105526 0.3331420 0.04870016 1.1144327713 3446.767 0.9988275\n", "a[46] -0.569168356 0.3490973 -1.14603518 -0.0001102425 4554.960 0.9988415\n", "a[47] 2.053672364 0.5490424 1.21890748 3.0052046403 4200.242 0.9989221\n", "a[48] 0.003217844 0.3466782 -0.55469935 0.5485189019 4947.435 0.9987783\n", "a_bar 1.351105699 0.2543945 0.94780768 1.7627148219 2829.865 1.0009259\n", "sigma 1.619300421 0.2201868 1.30942421 1.9943555871 1471.004 1.0029568" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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EMmgoNeZZ9ynl1Esw7wedTVgRevqu9DcNDDL7mBJNAAphIEB0gCwaESBAdIAtWB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\neBiCg1olgmN9WN+t5099W69NAeF6w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M7KShs9OkJf31w20rTppLCwdYcOjbx5s6GbmyiOq7RrN7Jy5TpffXVETe2/X+wW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" }, "metadata": { "filenames": { "image/png": "/tmp/_build/jupyter_execute/notes/practice-13_29_2.png" } }, "output_type": "display_data" } ], "source": [ "data(reedfrogs)\n", "rf_df <- reedfrogs\n", "rf_df$tank <- 1:nrow(rf_df)\n", "\n", "rf_dat <- list(\n", " S = rf_df$surv,\n", " N = rf_df$density,\n", " tank = rf_df$tank\n", ")\n", "\n", "## R code 13.3\n", "m13.2 <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank],\n", " a[tank] ~ dnorm(a_bar, sigma),\n", " a_bar ~ dnorm(0, 1.5),\n", " sigma ~ dexp(1)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE\n", ")\n", "\n", "plot_means <- function(post, plot_main) {\n", " # compute mean intercept for each tank\n", " # also transform to probability with logistic\n", " rf_df$propsurv.est <- logistic(apply(post$a, 2, mean))\n", "\n", " iplot(function() {\n", " # display raw proportions surviving in each tank\n", " plot(rf_df$propsurv,\n", " ylim = c(0, 1), pch = 16, xaxt = \"n\",\n", " xlab = \"tank\", ylab = \"proportion survival\", col = rangi2,\n", " main=plot_main\n", " )\n", " axis(1, at = c(1, 16, 32, 48), labels = c(1, 16, 32, 48))\n", "\n", " # overlay posterior means\n", " points(rf_df$propsurv.est)\n", "\n", " # mark posterior mean probability across tanks\n", " abline(h = mean(inv_logit(post$a_bar)), lty = 2)\n", "\n", " # draw vertical dividers between tank densities\n", " abline(v = 16.5, lwd = 0.5)\n", " abline(v = 32.5, lwd = 0.5)\n", " text(8, 0, \"small tanks\")\n", " text(16 + 8, 0, \"medium tanks\")\n", " text(32 + 8, 0, \"large tanks\")\n", " })\n", "}\n", "\n", "display(precis(m13.2, depth = 2), mimetypes=\"text/plain\")\n", "iplot(function() {\n", " plot(precis(m13.2, depth=2), main='m13.2')\n", "}, ar=1.0)\n", "post <- extract.samples(m13.2)\n", "plot_means(post, \"m13.2\")" ] }, { "cell_type": "markdown", "id": "b7aa0327", "metadata": {}, "source": [ "As promised, sampling from the model produces divergent transitions:" ] }, { "cell_type": "code", "execution_count": 16, "id": "0ea4fa95", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“There were 130 divergent transitions after warmup. See\n", "https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup\n", "to find out why this is a problem and how to eliminate them.”\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“Examine the pairs() plot to diagnose sampling problems\n", "”\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.\n", "Running the chains for more iterations may help. See\n", "https://mc-stan.org/misc/warnings.html#bulk-ess”\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.\n", "Running the chains for more iterations may help. See\n", "https://mc-stan.org/misc/warnings.html#tail-ess”\n" ] } ], "source": [ "m_tank_cauchy_orig <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank],\n", " a[tank] ~ dcauchy(a_bar, sigma),\n", " a_bar ~ dnorm(0, 1),\n", " sigma ~ dexp(1)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE\n", ")" ] }, { "cell_type": "markdown", "id": "75f69f2d", "metadata": {}, "source": [ "Adjusting `adapt_delta` does little to reduce the number of divergent transitions:" ] }, { "cell_type": "code", "execution_count": 17, "id": "35cab001", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "recompiling to avoid crashing R session\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“There were 94 divergent transitions after warmup. See\n", "https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup\n", "to find out why this is a problem and how to eliminate them.”\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“Examine the pairs() plot to diagnose sampling problems\n", "”\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.\n", "Running the chains for more iterations may help. See\n", "https://mc-stan.org/misc/warnings.html#bulk-ess”\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Warning message:\n", "“Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.\n", "Running the chains for more iterations may help. See\n", "https://mc-stan.org/misc/warnings.html#tail-ess”\n" ] } ], "source": [ "m_tank_cauchy <- ulam(\n", " alist(\n", " S ~ dbinom(N, p),\n", " logit(p) <- a[tank],\n", " a[tank] ~ dcauchy(a_bar, sigma),\n", " a_bar ~ dnorm(0, 1),\n", " sigma ~ dexp(1)\n", " ),\n", " data = rf_dat, chains = 4, cores = 4, log_lik = TRUE, control=list(adapt_delta=0.99)\n", ")" ] }, { "cell_type": "markdown", "id": "ad2c1684", "metadata": {}, "source": [ "Let's examine the `pairs()` plot suggested in the warning message (for only a few parameters):" ] }, { "cell_type": "code", "execution_count": 18, "id": "f2a228c0", "metadata": {}, "outputs": [ { "data": { "image/png": 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7riiituuummje1ZXGj/+q//eskll/zmb/4mPUdvvvnmV7ziFQD27Nlz//vff6uH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\npgVQUbsVvR8GMlQCWGbSlocm7rEFk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nnQj7mBdS0MjzX4mHHgnszNEhHwKwbc3PHwBorUkMBDQAACAASURBVJtOsZ+3eyt6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\nRZyTA7+HWMk/J02pl8VGhnYiBwOW2L8hhlu6ALhrrTh80ledU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GbDx3kqDBPSOGXT/Hi8ZCUahTmjD+BgZbPgvFnCepXfYb74HCMxhS0M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\nGvTspF4FfX4DaZgdAGqjolCJWh5C30XDIdS21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si2cLKnP6lfytA76iem4XgK8kbOqagrOUuUZskPCO2s8M6ytKszwRlypgfQWrYGd8YM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\n0pd+/dd//fU+xtVOlynMK