{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "ZJhD80bfN7ly" }, "source": [ "# Bayesian Regression Using NumPyro\n", "\n", "In this tutorial, we will explore how to do bayesian regression in NumPyro, using a simple example adapted from Statistical Rethinking [[1](#References)]. In particular, we would like to explore the following:\n", "\n", " - Write a simple model using the `sample` NumPyro primitive.\n", " - Run inference using MCMC in NumPyro, in particular, using the No U-Turn Sampler (NUTS) to get a posterior distribution over our regression parameters of interest.\n", " - Learn about inference utilities such as `Predictive` and `log_likelihood`.\n", " - Learn how we can use effect-handlers in NumPyro to generate execution traces from the model, condition on sample statements, seed models with RNG seeds, etc., and use this to implement various utilities that will be useful for MCMC. e.g. computing model log likelihood, generating empirical distribution over the posterior predictive, etc.\n", "\n", "## Tutorial Outline:\n", "\n", "1. [Dataset](#Dataset)\n", "2. [Regression Model to Predict Divorce Rate](#Regression-Model-to-Predict-Divorce-Rate)\n", " - [Model-1: Predictor-Marriage Rate](#Model-1:-Predictor---Marriage-Rate)\n", " - [Posterior Distribution over the Regression Parameters](#Posterior-Distribution-over-the-Regression-Parameters)\n", " - [Prior Predictive Distribution](#Prior-Predictive-Distribution)\n", " - [Posterior Predictive Distribution](#Posterior-Predictive-Distribution)\n", " - [Predictive Utility With Effect Handlers](#Predictive-Utility-With-Effect-Handlers)\n", " - [Posterior Predictive Density](#Posterior-Predictive-Density)\n", " - [Model-2: Predictor-Median Age of Marriage](#Model-2:-Predictor---Median-Age-of-Marriage)\n", " - [Model-3: Predictor-Marriage Rate and Median Age of Marriage](#Model-3:-Predictor---Marriage-Rate-and-Median-Age-of-Marriage)\n", " - [Divorce Rate Residuals by State](#Divorce-Rate-Residuals-by-State)\n", "3. [Regression Model with Measurement Error](#Regression-Model-with-Measurement-Error)\n", " - [Effect of Incorporating Measurement Noise on Residuals](#Effect-of-Incorporating-Measurement-Noise-on-Residuals)\n", "4. [References](#References)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "id": "FlhcyvtqN7l1" }, "outputs": [], "source": [ "!pip install -q numpyro@git+https://github.com/pyro-ppl/numpyro" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "id": "B_9Gru7DN7l3" }, "outputs": [], "source": [ "import os\n", "\n", "from IPython.display import set_matplotlib_formats\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import seaborn as sns\n", "\n", "from jax import random, vmap\n", "import jax.numpy as jnp\n", "from jax.scipy.special import logsumexp\n", "\n", "import numpyro\n", "from numpyro import handlers\n", "from numpyro.diagnostics import hpdi\n", "import numpyro.distributions as dist\n", "from numpyro.infer import MCMC, NUTS\n", "\n", "plt.style.use(\"bmh\")\n", "if \"NUMPYRO_SPHINXBUILD\" in os.environ:\n", " set_matplotlib_formats(\"svg\")\n", "\n", "assert numpyro.__version__.startswith(\"0.14.0\")" ] }, { "cell_type": "markdown", "metadata": { "id": "YfP23JA7N7l3" }, "source": [ "## Dataset\n", "\n", "For this example, we will use the `WaffleDivorce` dataset from Chapter 05, Statistical Rethinking [[1](#References)]. The dataset contains divorce rates in each of the 50 states in the USA, along with predictors such as population, median age of marriage, whether it is a Southern state and, curiously, number of Waffle Houses." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "KsCe9ruUN7l4", "outputId": "f26f9596-9f21-46d6-ec58-33dfc92b58a0" }, "outputs": [ { "data": { "text/html": [ "
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LocationLocPopulationMedianAgeMarriageMarriageMarriage SEDivorceDivorce SEWaffleHousesSouthSlaves1860Population1860PropSlaves1860
0AlabamaAL4.7825.320.21.2712.70.7912814350809642010.450000
1AlaskaAK0.7125.226.02.9312.52.0500000.000000
2ArizonaAZ6.3325.820.30.9810.80.74180000.000000
3ArkansasAR2.9224.326.41.7013.51.224111111154354500.260000
4CaliforniaCA37.2526.819.10.398.00.240003799940.000000
5ColoradoCO5.0325.723.51.2411.60.941100342770.000000
6ConnecticutCT3.5727.617.11.066.70.770004601470.000000
7DelawareDE0.9026.623.12.898.91.393017981122160.016000
8District of ColumbiaDC0.6029.717.72.536.31.89000750800.000000
9FloridaFL18.8026.417.00.588.50.321331617451404240.440000
10GeorgiaGA9.6925.922.10.8111.50.58381146219810572860.440000
11HawaiiHI1.3626.924.92.548.31.2700000.000000
12IdahoID1.5723.225.81.847.71.0500000.000000
13IllinoisIL12.8327.017.90.588.00.4520017119510.000000
14IndianaIN6.4825.719.80.8111.00.63170013504280.000000
15IowaIA3.0525.421.51.4610.20.910006749130.000000
16KansasKS2.8525.022.11.4810.61.096021072060.000019
17KentuckyKY4.3424.822.21.1112.60.7564122548311556840.000000
18LouisianaLA4.5325.920.61.1911.00.896613317267080020.470000
19MaineME1.3326.413.51.4013.01.480006282790.000000
20MarylandMD5.7727.318.31.028.80.69110871896870490.130000
21MassachusettsMA6.5528.515.80.707.80.5200012310660.000000
22MichiganMI9.8826.416.50.699.20.530007491130.000000
23MinnesotaMN5.3026.315.30.777.40.600001720230.000000
24MississippiMS2.9725.819.31.5411.11.017214366317913050.550000
25MissouriMO5.9925.618.60.819.50.6739111493111820120.097000
26MontanaMT0.9925.718.52.319.11.7100000.000000
27NebraskaNE1.8325.419.61.448.80.940015288410.000520
28New HampshireNH1.3226.816.71.7610.11.610003260730.000000
29New JerseyNJ8.7927.714.80.596.10.4600186720350.000027
30New MexicoNM2.0625.820.41.9010.21.11200935160.000000
31New YorkNY19.3828.416.80.476.60.3100038807350.000000
32North CarolinaNC9.5425.720.40.989.90.4814213310599926220.330000
33North DakotaND0.6725.326.72.938.01.4400000.000000
34OhioOH11.5426.316.90.619.50.45640023395110.000000
35OklahomaOK3.7524.423.81.2912.81.01160000.000000
36OregonOR3.8326.018.91.1010.40.80000524650.000000
37PennsylvaniaPA12.7027.115.50.487.70.43110029062150.000000
38Rhode IslandRI1.0528.215.02.119.41.790001746200.000000
39South CarolinaSC4.6326.418.11.188.10.7014414024067037080.570000
40South DakotaSD0.8125.620.12.6410.92.5000048370.000000
41TennesseeTN6.3525.219.40.8511.40.75103127571911098010.200000
42TexasTX25.1525.221.50.6110.00.359911825666042150.300000
43UtahUT2.7623.329.61.7710.20.93000402730.000000
44VermontVT0.6326.916.42.409.61.870003150980.000000
45VirginiaVA8.0026.420.50.838.90.5240149086512196300.400000
46WashingtonWA6.7225.921.41.0010.00.65000115940.000000
47West VirginiaWV1.8525.022.21.6910.91.3441183713766880.049000
48WisconsinWI5.6926.317.20.798.30.570007758810.000000
49WyomingWY0.5624.230.73.9210.31.9000000.000000
\n", "
" ], "text/plain": [ " Location Loc ... Population1860 PropSlaves1860\n", "0 Alabama AL ... 964201 0.450000\n", "1 Alaska AK ... 0 0.000000\n", "2 Arizona AZ ... 0 0.000000\n", "3 Arkansas AR ... 435450 0.260000\n", "4 California CA ... 379994 0.000000\n", "5 Colorado CO ... 34277 0.000000\n", "6 Connecticut CT ... 460147 0.000000\n", "7 Delaware DE ... 112216 0.016000\n", "8 District of Columbia DC ... 75080 0.000000\n", "9 Florida FL ... 140424 0.440000\n", "10 Georgia GA ... 1057286 0.440000\n", "11 Hawaii HI ... 0 0.000000\n", "12 Idaho ID ... 0 0.000000\n", "13 Illinois IL ... 1711951 0.000000\n", "14 Indiana IN ... 1350428 0.000000\n", "15 Iowa IA ... 674913 0.000000\n", "16 Kansas KS ... 107206 0.000019\n", "17 Kentucky KY ... 1155684 0.000000\n", "18 Louisiana LA ... 708002 0.470000\n", "19 Maine ME ... 628279 0.000000\n", "20 Maryland MD ... 687049 0.130000\n", "21 Massachusetts MA ... 1231066 0.000000\n", "22 Michigan MI ... 749113 0.000000\n", "23 Minnesota MN ... 172023 0.000000\n", "24 Mississippi MS ... 791305 0.550000\n", "25 Missouri MO ... 1182012 0.097000\n", "26 Montana MT ... 0 0.000000\n", "27 Nebraska NE ... 28841 0.000520\n", "28 New Hampshire NH ... 326073 0.000000\n", "29 New Jersey NJ ... 672035 0.000027\n", "30 New Mexico NM ... 93516 0.000000\n", "31 New York NY ... 3880735 0.000000\n", "32 North Carolina NC ... 992622 0.330000\n", "33 North Dakota ND ... 0 0.000000\n", "34 Ohio OH ... 2339511 0.000000\n", "35 Oklahoma OK ... 0 0.000000\n", "36 Oregon OR ... 52465 0.000000\n", "37 Pennsylvania PA ... 2906215 0.000000\n", "38 Rhode Island RI ... 174620 0.000000\n", "39 South Carolina SC ... 703708 0.570000\n", "40 South Dakota SD ... 4837 0.000000\n", "41 Tennessee TN ... 1109801 0.200000\n", "42 Texas TX ... 604215 0.300000\n", "43 Utah UT ... 40273 0.000000\n", "44 Vermont VT ... 315098 0.000000\n", "45 Virginia VA ... 1219630 0.400000\n", "46 Washington WA ... 11594 0.000000\n", "47 West Virginia WV ... 376688 0.049000\n", "48 Wisconsin WI ... 775881 0.000000\n", "49 Wyoming WY ... 0 0.000000\n", "\n", "[50 rows x 13 columns]" ] }, "execution_count": 3, "metadata": { "tags": [] }, "output_type": "execute_result" } ], "source": [ "DATASET_URL = \"https://raw.githubusercontent.com/rmcelreath/rethinking/master/data/WaffleDivorce.csv\"\n", "dset = pd.read_csv(DATASET_URL, sep=\";\")\n", "dset" ] }, { "cell_type": "markdown", "metadata": { "id": "Hu-1n8UfN7l6" }, "source": [ "Let us plot the pair-wise relationship amongst the main variables in the dataset, using `seaborn.pairplot`. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "pNjxHdVvN7l6", "outputId": "eb113ed4-bc40-45f5-e82d-c56142336227" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "vars = [\n", " \"Population\",\n", " \"MedianAgeMarriage\",\n", " \"Marriage\",\n", " \"WaffleHouses\",\n", " \"South\",\n", " \"Divorce\",\n", "]\n", "sns.pairplot(dset, x_vars=vars, y_vars=vars, palette=\"husl\");" ] }, { "cell_type": "markdown", "metadata": { "id": "Nzqje01_N7l7" }, "source": [ "From the plots above, we can clearly observe that there is a relationship between divorce rates and marriage rates in a state (as might be expected), and also between divorce rates and median age of marriage. \n", "\n", "There is also a weak relationship between number of Waffle Houses and divorce rates, which is not obvious from the plot above, but will be clearer if we regress `Divorce` against `WaffleHouse` and plot the results. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 279 }, "id": "jBhug-OzN7l8", "outputId": "9f95c298-43e7-4f40-cde5-0a9364088980" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "sns.regplot(x=\"WaffleHouses\", y=\"Divorce\", data=dset);" ] }, { "cell_type": "markdown", "metadata": { "id": "Kc4rautdN7l9" }, "source": [ "This is an example of a spurious association. We do not expect the number of Waffle Houses in a state to affect the divorce rate, but it is likely correlated with other factors that have an effect on the divorce rate. We will not delve into this spurious association in this tutorial, but the interested reader is encouraged to read Chapters 5 and 6 of [[1](#References)] which explores the problem of causal association in the presence of multiple predictors. \n", "\n", "For simplicity, we will primarily focus on marriage rate and the median age of marriage as our predictors for divorce rate throughout the remaining tutorial." ] }, { "cell_type": "markdown", "metadata": { "id": "mQuCSnFLN7l9" }, "source": [ "## Regression Model to Predict Divorce Rate\n", "\n", "Let us now write a regressionn model in *NumPyro* to predict the divorce rate as a linear function of marriage rate and median age of marriage in each of the states. \n", "\n", "First, note that our predictor variables have somewhat different scales. It is a good practice to standardize our predictors and response variables to mean `0` and standard deviation `1`, which should result in [faster inference](https://mc-stan.org/docs/2_19/stan-users-guide/standardizing-predictors-and-outputs.html)." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "CPtcs7a6N7l-" }, "outputs": [], "source": [ "def standardize(x):\n", " return (x - x.mean()) / x.std()\n", "\n", "\n", "dset[\"AgeScaled\"] = dset.MedianAgeMarriage.pipe(standardize)\n", "dset[\"MarriageScaled\"] = dset.Marriage.pipe(standardize)\n", "dset[\"DivorceScaled\"] = dset.Divorce.pipe(standardize)" ] }, { "cell_type": "markdown", "metadata": { "id": "olBAKjb1N7l-" }, "source": [ "We write the NumPyro model as follows. While the code should largely be self-explanatory, take note of the following:\n", "\n", " - In NumPyro, *model* code is any Python callable which can optionally accept additional arguments and keywords. For HMC which we will be using for this tutorial, these arguments and keywords remain static during inference, but we can reuse the same model to generate [predictions](#Posterior-Predictive-Distribution) on new data.\n", " - In addition to regular Python statements, the model code also contains primitives like `sample`. These primitives can be interpreted with various side-effects using effect handlers. For more on effect handlers, refer to [[3](#References)], [[4](#References)]. For now, just remember that a `sample` statement makes this a stochastic function that samples some latent parameters from a *prior distribution*. Our goal is to infer the *posterior distribution* of these parameters conditioned on observed data.\n", " - The reason why we have kept our predictors as optional keyword arguments is to be able to reuse the same model as we vary the set of predictors. Likewise, the reason why the response variable is optional is that we would like to reuse this model to sample from the posterior predictive distribution. See the [section](#Posterior-Predictive-Distribution) on plotting the posterior predictive distribution, as an example." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "id": "hVzAKfmnN7l-" }, "outputs": [], "source": [ "def model(marriage=None, age=None, divorce=None):\n", " a = numpyro.sample(\"a\", dist.Normal(0.0, 0.2))\n", " M, A = 0.0, 0.0\n", " if marriage is not None:\n", " bM = numpyro.sample(\"bM\", dist.Normal(0.0, 0.5))\n", " M = bM * marriage\n", " if age is not None:\n", " bA = numpyro.sample(\"bA\", dist.Normal(0.0, 0.5))\n", " A = bA * age\n", " sigma = numpyro.sample(\"sigma\", dist.Exponential(1.0))\n", " mu = a + M + A\n", " numpyro.sample(\"obs\", dist.Normal(mu, sigma), obs=divorce)" ] }, { "cell_type": "markdown", "metadata": { "id": "tsUGIXf4N7l_" }, "source": [ "### Model 1: Predictor - Marriage Rate\n", "\n", "We first try to model the divorce rate as depending on a single variable, marriage rate. As mentioned above, we can use the same `model` code as earlier, but only pass values for `marriage` and `divorce` keyword arguments. We will use the No U-Turn Sampler (see [[5](#References)] for more details on the NUTS algorithm) to run inference on this simple model.\n", "\n", "The Hamiltonian Monte Carlo (or, the NUTS) implementation in NumPyro takes in a potential energy function. This is the negative log joint density for the model. Therefore, for our model description above, we need to construct a function which given the parameter values returns the potential energy (or negative log joint density). Additionally, the verlet integrator in HMC (or, NUTS) returns sample values simulated using Hamiltonian dynamics in the unconstrained space. As such, continuous variables with bounded support need to be transformed into unconstrained space using bijective transforms. We also need to transform these samples back to their constrained support before returning these values to the user. Thankfully, this is handled on the backend for us, within a convenience class for doing [MCMC inference](https://numpyro.readthedocs.io/en/latest/mcmc.html#numpyro.mcmc.MCMC) that has the following methods:\n", "\n", " - `run(...)`: runs warmup, adapts steps size and mass matrix, and does sampling using the sample from the warmup phase.\n", " - `print_summary()`: print diagnostic information like quantiles, effective sample size, and the Gelman-Rubin diagnostic.\n", " - `get_samples()`: gets samples from the posterior distribution.\n", "\n", "Note the following:\n", "\n", " - JAX uses functional PRNGs. Unlike other languages / frameworks which maintain a global random state, in JAX, every call to a sampler requires an [explicit PRNGKey](https://github.com/google/jax#random-numbers-are-different). We will split our initial random seed for subsequent operations, so that we do not accidentally reuse the same seed.\n", " - We run inference with the `NUTS` sampler. To run vanilla HMC, we can instead use the [HMC](https://numpyro.readthedocs.io/en/latest/mcmc.html#numpyro.mcmc.HMC) class." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "er7-QqEhN7l_", "outputId": "d52e722b-0061-49a1-d9df-d977a311b88d" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sample: 100%|██████████| 3000/3000 [00:04<00:00, 748.14it/s, 7 steps of size 7.41e-01. acc. prob=0.92]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " mean std median 5.0% 95.0% n_eff r_hat\n", " a 0.00 0.11 0.00 -0.16 0.20 1510.96 1.00\n", " bM 0.35 0.13 0.35 0.14 0.57 2043.12 1.00\n", " sigma 0.95 0.10 0.94 0.78 1.10 1565.40 1.00\n", "\n", "Number of divergences: 0\n" ] } ], "source": [ "# Start from this source of randomness. We will split keys for subsequent operations.\n", "rng_key = random.PRNGKey(0)\n", "rng_key, rng_key_ = random.split(rng_key)\n", "\n", "# Run NUTS.\n", "kernel = NUTS(model)\n", "num_samples = 2000\n", "mcmc = MCMC(kernel, num_warmup=1000, num_samples=num_samples)\n", "mcmc.run(\n", " rng_key_, marriage=dset.MarriageScaled.values, divorce=dset.DivorceScaled.values\n", ")\n", "mcmc.print_summary()\n", "samples_1 = mcmc.get_samples()" ] }, { "cell_type": "markdown", "metadata": { "id": "0IfifzKHN7mA" }, "source": [ "#### Posterior Distribution over the Regression Parameters\n", "\n", "We notice that the progress bar gives us online statistics on the acceptance probability, step size and number of steps taken per sample while running NUTS. In particular, during warmup, we adapt the step size and mass matrix to achieve a certain target acceptance probability which is 0.8, by default. We were able to successfully adapt our step size to achieve this target in the warmup phase.\n", "\n", "During warmup, the aim is to adapt hyper-parameters such as step size and mass matrix (the HMC algorithm is very sensitive to these hyper-parameters), and to reach the typical set (see [[6](#References)] for more details). If there are any issues in the model specification, the first signal to notice would be low acceptance probabilities or very high number of steps. We use the sample from the end of the warmup phase to seed the MCMC chain (denoted by the second `sample` progress bar) from which we generate the desired number of samples from our target distribution.\n", "\n", "At the end of inference, NumPyro prints the mean, std and 90% CI values for each of the latent parameters. Note that since we standardized our predictors and response variable, we would expect the intercept to have mean 0, as can be seen here. It also prints other convergence diagnostics on the latent parameters in the model, including [effective sample size](https://numpyro.readthedocs.io/en/latest/diagnostics.html#numpyro.diagnostics.effective_sample_size) and the [gelman rubin diagnostic](https://numpyro.readthedocs.io/en/latest/diagnostics.html#numpyro.diagnostics.gelman_rubin) ($\\hat{R}$). The value for these diagnostics indicates that the chain has converged to the target distribution. In our case, the \"target distribution\" is the posterior distribution over the latent parameters that we are interested in. Note that this is often worth verifying with multiple chains for more complicated models. In the end, `samples_1` is a collection (in our case, a `dict` since `init_samples` was a `dict`) containing samples from the posterior distribution for each of the latent parameters in the model.\n", "\n", "To look at our regression fit, let us plot the regression line using our posterior estimates for the regression parameters, along with the 90% Credibility Interval (CI). Note that the [hpdi](https://numpyro.readthedocs.io/en/latest/diagnostics.html#numpyro.diagnostics.hpdi) function in NumPyro's diagnostics module can be used to compute CI. In the functions below, note that the collected samples from the posterior are all along the leading axis." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 405 }, "id": "UX-DbOtsN7mA", "outputId": "163ad2c9-7567-490f-9535-f6834f457c8a" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "def plot_regression(x, y_mean, y_hpdi):\n", " # Sort values for plotting by x axis\n", " idx = jnp.argsort(x)\n", " marriage = x[idx]\n", " mean = y_mean[idx]\n", " hpdi = y_hpdi[:, idx]\n", " divorce = dset.DivorceScaled.values[idx]\n", "\n", " # Plot\n", " fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(6, 6))\n", " ax.plot(marriage, mean)\n", " ax.plot(marriage, divorce, \"o\")\n", " ax.fill_between(marriage, hpdi[0], hpdi[1], alpha=0.3, interpolate=True)\n", " return ax\n", "\n", "\n", "# Compute empirical posterior distribution over mu\n", "posterior_mu = (\n", " jnp.expand_dims(samples_1[\"a\"], -1)\n", " + jnp.expand_dims(samples_1[\"bM\"], -1) * dset.MarriageScaled.values\n", ")\n", "\n", "mean_mu = jnp.mean(posterior_mu, axis=0)\n", "hpdi_mu = hpdi(posterior_mu, 0.9)\n", "ax = plot_regression(dset.MarriageScaled.values, mean_mu, hpdi_mu)\n", "ax.set(\n", " xlabel=\"Marriage rate\", ylabel=\"Divorce rate\", title=\"Regression line with 90% CI\"\n", ");" ] }, { "cell_type": "markdown", "metadata": { "id": "sndvig_RQi0s" }, "source": [ "We can see from the plot, that the CI broadens towards the tails where the data is relatively sparse, as can be expected.\n", "\n", "#### Prior Predictive Distribution\n", "\n", "Let us check that we have set sensible priors by sampling from the prior predictive distribution. NumPyro provides a handy [Predictive](http://num.pyro.ai/en/latest/utilities.html#numpyro.infer.util.Predictive) utility for this purpose." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 405 }, "id": "vSfDasR7Q5Be", "outputId": "a11554aa-96b7-4298-9456-d44e0d63d8af" }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "from numpyro.infer import Predictive\n", "\n", "rng_key, rng_key_ = random.split(rng_key)\n", "prior_predictive = Predictive(model, num_samples=100)\n", "prior_predictions = prior_predictive(rng_key_, marriage=dset.MarriageScaled.values)[\n", " \"obs\"\n", "]\n", "mean_prior_pred = jnp.mean(prior_predictions, axis=0)\n", "hpdi_prior_pred = hpdi(prior_predictions, 0.9)\n", "\n", "ax = plot_regression(dset.MarriageScaled.values, mean_prior_pred, hpdi_prior_pred)\n", "ax.set(xlabel=\"Marriage rate\", ylabel=\"Divorce rate\", title=\"Predictions with 90% CI\");" ] }, { "cell_type": "markdown", "metadata": { "id": "Q1ojeyHpN7mB" }, "source": [ "#### Posterior Predictive Distribution\n", "\n", "Let us now look at the posterior predictive distribution to see how our predictive distribution looks with respect to the observed divorce rates. To get samples from the posterior predictive distribution, we need to run the model by substituting the latent parameters with samples from the posterior. Note that by default we generate a single prediction for each sample from the joint posterior distribution, but this can be controlled using the `num_samples` argument." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "XzzsqL7jN7mB", "outputId": "00bb95d0-8be6-4686-f9d9-bc8a8891aa2c" }, "outputs": [ { "data": { "text/html": [ "
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LocationMean Predictions
0Alabama0.016434
1Alaska0.501293
2Arizona0.025105
3Arkansas0.600058
4California-0.082887
\n", "
" ], "text/plain": [ " Location Mean Predictions\n", "0 Alabama 0.016434\n", "1 Alaska 0.501293\n", "2 Arizona 0.025105\n", "3 Arkansas 0.600058\n", "4 California -0.082887" ] }, "execution_count": 11, "metadata": { "tags": [] }, "output_type": "execute_result" } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "predictive = Predictive(model, samples_1)\n", "predictions = predictive(rng_key_, marriage=dset.MarriageScaled.values)[\"obs\"]\n", "df = dset.filter([\"Location\"])\n", "df[\"Mean Predictions\"] = jnp.mean(predictions, axis=0)\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": { "id": "n-Sm_5H8N7mC" }, "source": [ "#### Predictive Utility With Effect Handlers\n", "\n", "To remove the magic behind `Predictive`, let us see how we can combine [effect handlers](https://numpyro.readthedocs.io/en/latest/handlers.html) with the [vmap](https://github.com/google/jax#auto-vectorization-with-vmap) JAX primitive to implement our own simplified predictive utility function that can do vectorized predictions." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "id": "gSKilj8dN7mC" }, "outputs": [], "source": [ "def predict(rng_key, post_samples, model, *args, **kwargs):\n", " model = handlers.seed(handlers.condition(model, post_samples), rng_key)\n", " model_trace = handlers.trace(model).get_trace(*args, **kwargs)\n", " return model_trace[\"obs\"][\"value\"]\n", "\n", "\n", "# vectorize predictions via vmap\n", "predict_fn = vmap(\n", " lambda rng_key, samples: predict(\n", " rng_key, samples, model, marriage=dset.MarriageScaled.values\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "hGB12J3-N7mC" }, "source": [ "Note the use of the `condition`, `seed` and `trace` effect handlers in the `predict` function.\n", "\n", " - The `seed` effect-handler is used to wrap a stochastic function with an initial `PRNGKey` seed. When a sample statement inside the model is called, it uses the existing seed to sample from a distribution but this effect-handler also splits the existing key to ensure that future `sample` calls in the model use the newly split key instead. This is to prevent us from having to explicitly pass in a `PRNGKey` to each `sample` statement in the model.\n", " - The `condition` effect handler conditions the latent sample sites to certain values. In our case, we are conditioning on values from the posterior distribution returned by MCMC.\n", " - The `trace` effect handler runs the model and records the execution trace within an `OrderedDict`. This trace object contains execution metadata that is useful for computing quantities such as the log joint density.\n", " \n", "It should be clear now that the `predict` function simply runs the model by substituting the latent parameters with samples from the posterior (generated by the `mcmc` function) to generate predictions. Note the use of JAX's auto-vectorization transform called [vmap](https://github.com/google/jax#auto-vectorization-with-vmap) to vectorize predictions. Note that if we didn't use `vmap`, we would have to use a native for loop which for each sample which is much slower. Each draw from the posterior can be used to get predictions over all the 50 states. When we vectorize this over all the samples from the posterior using `vmap`, we will get a `predictions_1` array of shape `(num_samples, 50)`. We can then compute the mean and 90% CI of these samples to plot the posterior predictive distribution. We note that our mean predictions match those obtained from the `Predictive` utility class." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "Hbo0AzmSN7mD", "outputId": "9183ecd2-bb3b-473b-e912-09188806573e" }, "outputs": [ { "data": { "text/html": [ "
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LocationMean Predictions
0Alabama0.016434
1Alaska0.501293
2Arizona0.025105
3Arkansas0.600058
4California-0.082887
\n", "
" ], "text/plain": [ " Location Mean Predictions\n", "0 Alabama 0.016434\n", "1 Alaska 0.501293\n", "2 Arizona 0.025105\n", "3 Arkansas 0.600058\n", "4 California -0.082887" ] }, "execution_count": 13, "metadata": { "tags": [] }, "output_type": "execute_result" } ], "source": [ "# Using the same key as we used for Predictive - note that the results are identical.\n", "\n", "predictions_1 = predict_fn(random.split(rng_key_, num_samples), samples_1)\n", "\n", "mean_pred = jnp.mean(predictions_1, axis=0)\n", "df = dset.filter([\"Location\"])\n", "df[\"Mean Predictions\"] = mean_pred\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 405 }, "id": "x57YjUCLN7mD", "outputId": "19ed4248-f852-40d1-da61-f06faa6c4cbd" }, "outputs": [ { "data": { "image/png": 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LC253wTMoLSy8pMVCTqNQMVjMVciW2/PVVw3JYk7j0YU83zub5cRayZYRAJB57xav7zV2x4WaEfiMZDLpdhc8g9LCwita6IbkdLrceP7MaokrZhMIIXb8W0NK1otVlvMV1oqVtnP7i4iqzVAnmUyqxWKFQmEPvXYHHgwIoqGA+QgKWxfwZs6kyxsWbvOazkJOY3Y4uu3fVXSD78/l0HTl33cDZQh8Ri6XY2Jiwu1ueAKlhUUnWuQ1nSeWC+ekWRYCosGaUQgJYnUDUXtENi0El6oGc9kymzm1XmZiKEw4GODsJ7/I8bvvoXRmkdi+aS65693svfkGnlktOWYEpFZExEccOZffyeVyttopQ+AzZmZm3O6CZ1BaWLSrxVy2zMm1Uks3jJTmxX2r6JxgoNlQBChU9JbnqRqSk+sl4l/7Bo/c+T6MomksSqcXeOTO95EtV1l92cvb6n8rREJtrKszMzOjks71I3YiAAYFpYXFbrWo6AaPL+V5drW1EbCDbkChYrBWrDKf1bYt1r6Yq/D4e+9pGIE6RrHMiT/48/Y6sAWysO7o+fyM3XGhZgQ+Y7c+235GaWGxGy0ypSpPLBd67o8vn11sedxYcNqgq3FRx+64UDMCnzE+Pu52FzyD0sLCjhZSmi6aRxfzrizKipnWex22Ot72+6j1gQZ2vyOeMARCiANCiK8KIR4VQhwTQvyS233yKsodYqG0sNhJi3LV4NGFPGfSZdcSscVuuwVim6KHYlHzuIMo15CF31xDVeDXpJTfE0IMA/cLIb4spXzU7Y55jZERdbdTR2lhsZ0WK/kKT68Wqba7GOAQkRuvA6Byz8eozi8hZqaI3XZL47hTiMhg5VzajpGREf/sI5BSzgFztd+zQojHgH2AMgSb0PXBzKveCqWFRSstdEPy7FqRxZx36hlHbrzO8Qv/OcjBKTyzE3a/I55wDTUjhDgEPA/4lrs98Sb5fN7tLngGpYXFZi3yms7D8zlPGYFeISslt7vgGex+RzwxI6gjhEgCnwR+WUq5oaLC4uIit956K6FQCF3Xuemmm7j99tuZn58nkUgQDAbJZDJMTU2xurqKlJKpqSkWFhYa2+9zuRwzMzMsLS0hhGB8fJylpSVGRkbQdZ18Ps/s7Czz8/OEw2FSqRTLy8ukUik0TaNYLDZej0QiDA8Ps7KywtjYGMVikVKp1Hg9FosRj8dZW1tjYmKCbDaLpmmN1+PxOJFIhHQ6zeTkJOl0mkql0nh9q880NjbGiRMn+uoztft/0nWds2fP9tVnavf/pOs65XKZ+fl5SoRY1QRGMYeIjyC1AuhVRHIcmVuFUBQRDCHLeUQ8hSznwNAbr4twDEQAqRUQQ6PIYgaQ5u/5tUYKB6kVEYmxmk9emO9VWDddM9JAVkrWewaCiGgSWUwjogmkXoVq2Xo9GEJEhswU0rEksqpBVWvqcwQRiiBLO38mokMY2eW++kz5fJBsJrPrsReLxexde72SvlYIEQY+B3xRSvmHm18/evSoPHz4cO875jFOnDjBwYMH3e6GJ1BaWJw4cYK9+w/w9GqR1cJgF2Ux0gsEUv212fCa80YItBEufeLECVZWVu6//vrrX7hdO0/MCIQZ7PoXwGOtjIDCIhwOu90Fz6C0sNAJqlw9dQKqfnMdu98Rr6wRvAx4B3CdEOLB2uO1bnfKi6RSKbe74BmUFtbegIVKWBmBGiLqjUysXsDud8QTMwIp5f9FbQe0xfLyMolEwu1ueIJB16JY0Xl6pUimrGMU0gRS9vzB/Y4sphERpQWY3xE7eMIQKOyj7oItBlULQ0rOpMuczZQbeYJEdHAN4maUFhapVMo/+wgU9tE0ze0ueIZB1GKtWOHZ1dI5GUGlXlVT6hpKCwu73xFlCHxGsVh0uwueoR+0kFKS03QypSqZsk5AQDgQIBwU5qP2e0DAmUx564ig6rl1AAYWpUUDu9+RvjcEWxXC8Cuzs7Nud8EzdFsLKaXtEou7Ce0rVQ3SxSrpkvlwIvWDSKoEfHWUFhazs7OqHsHZT36RR+58H6XTCyBloxDG2U9+0e2utc38/LzbXfAM3dbiTMbenaWmS7bbj1M1JCuFCk+vFHngTJYHzmR5erXISqHiWP4fmVt15Dz9gNLCwu53pK9nBMfvbl0I4/jd9/h2VhCJRNzugmfothbpYpVwQGNmePv3kVJS0SESMmcFhpTkyjrrpSqZUpWcpnc/42ewr7/Ku0Np0cDud6SvFSudaV0IY6vjfmB4eNjtLniGXmhxYr1IKh4iFtp+8lyqGlQMyan1EplyFb3Hec9Uxk0LpYXF8PAwc3NzO7bra9dQbN/0ro77ATv+vkGhF1roBjy1UtixnaYb5DWdtWLvjQBQy52jAKVFM3a/I31tCC65690E4hsLYQTiUS65690u9ahzxsZUYe46vdIiU9KZ22G9oLxFgfdeIWJqN20dpYWF3e9IXxuCvTffwOXv/01i+2dACGL7Z7j8/b/p2/UB6I+QSafYSYvjSwVWCs6kYT6VLlGsbJ3bfXNcf6+R1cHbU7EVSgsLFT5aY+/NN/j6wr+ZUknlWq+znRZVQ7JarLBSqDASC3JoLE4i0n4yMtNFVOTITKJlSGmv8/xo995H6c8+hlwwK31FbnkTsZve3NM+eBZlCBrYvV709YygH1H7CCy20yJbqjYidTIlne/P5XhyuYDWwZ17tqxzNtP6ItNL15B2730U7/4gcn4RpETOL1L+44+h3Xtfz/rgZdQ+Agu71wtlCHyG2kdgsZ0WmfK5O3CX8hUenMtyar2E3mb8/ul0iYJ2rouol4ag9Gcfg9KmNYty2TyuUPsImrB7vVCGwGfYrTjU75z95Bd58k13cO+el/G1F775nE2CmXJrf75uwOl0mQfPZlnM7d6FYEh4cqV4zgYyQ0KlR+4hubC0q+MDR0jttalj93qhDIHPiMfjbnfBdeo7xitzSy13jOuGJN/irr0ZTZc8tVLk+3M5MqXdVfTKazqn0+dGEfVqViBmpnZ1fNAQyhA0sHu9UIbAZ6ytrbndBdfZcsf4e+8BIFuu2t7Jm9d0ji3keXwpv21U0GbOZMrnGJtyjzYQxG67BWIbw6KJRszjCmQp53YXPIPd64UyBD5jYmLC7S70FN2QrBc3hoBuuWP8rHk8vcs7fIDVQpXvz+V4dq1oK/+PlPDkcgGjZnG0e+/j1A1vI/3i15J54y1dXbiN3Hgd8bvuQMxOgxCI2Wliv/7vidx4Xdfe00+I+IjbXfAMdq8XfR8+2m9ks1mSycHZMHM6XWIuq3EgFWNfyrwLju2bNhMJbiKydxpDSpby7e0dMCTMZTSKFYNLp3cublKoGJxeL2N8+asU7/5gYwFXzi+az6FrF+fIjddtOLeRUzvO60itgIgoFyqY1ws7qBmBzxikYiy5cpW5rIaUcHK91LgD32rH+J5ffRdrxWrHi7brxSrZFlFHrTibLfP0+z58bhRPqcdRPPruZ0F9i9Kigd3rhTIEPmNQ9hEYUvL0anGDr38pX+HYQp7JN76ay9//m0T3bdwxnnjd9W1FArWi1WJwK6QEba61q6qXUTwqdt5CaWFh93qhXEM+Y35+noMHD7rdja4zlymT185dfM2VdR6ez3HghleSPHwBVxw6yGTCjBI5tpAju0XY6G5ZL1YJBewVmxEzU+bmrhbHe4XMrSJSMz17v+3YvOs5dtstPV2/8JIWbqP2EfQp/Rg+akgz3LNY0SlXDXLl6rZ35PXQT01EKFRMYyGlJFt2Nu+/3aIxLaN4YtHeRvGEoju36QGtdj0X7/5gb3c9e0QLL2D3eqFmBD6j3wrTrBUqPLteolTZfeilCIYaIZ8VXXa/+MsW1O923bwLFh4pxtJy13NtvaRXenhFCy+gCtP0Kel0mtHRUbe74QhVQ/LESqHt/P2ynKdQMUMF3c7+uTmKp9fIct4T6Ze9sOvZK1p4gXQ6baudcg35jMnJSbe74BgLWa2jIi4inqJcNdAN2bP0Dl5FxFNudwHwxq5nr2jhBexeL5Qh8Bl2LbzXMaRkPmsvMmcrZDmHlOZsoFe7er2KLHtjN60X1ku8ooUXsHu9UK4hn1GpOFNoxW1WCpXOc/gb5vpAobbIPNAYzkRLdYoX1ku8ooUXsHu9UIbAZ/hpH4EhJXOZMpouOX98Y/TCTqUf7VCPFy9qBtqAzwi8FDvv9nqJl7Rwm9nZWVt1i5VryGf4pR7BerHC9+dynFwvM5/VNhSAXy9WWu4R2C31vPN5NSNQOfibUFpYqH0EfUoisXMOHDeo35FrVYPjywUeWyxQbAoJXcxVGsZgLuvM7l8RNnOtm/sPBnyxOKzqVNRRWljYvV4o15DPCAbbr7vbLVbyFY4vFxgKByjrxpaRQIu5ClUjz3rRoVwwwryPGXQjADS0UKC0aMLu9UIp5jMymYzbXdhARTd4Zq0ImNk4d3LVrxacSwgmtcLOjQYEpYWF0sLC7vVCGQKfMTXlrSpUz6yVXIvhF0P9sbHOCZQWFkoLC7vXC+Ua8hmrq6sMDQ05ft6KbrBcqJAv6+hSUjUk4UCACyfiBLdIvrZSqLDSZu5/J5DFDCLsLcPoFkoLC6WFxeqqvYVzZQh8xuai6Z1gSMlaocpSXmO91Kq8o45EcsnkEEJsNAYV3eCZ1aJjfWkPtTZgobSwUFrUsXu9UIbAZ3TqGpJSkinrLOc1VgoVWz79p1eLXDhhzULSpSon1oqup3VQLgALpYWF0sJiamqKpaWd8zwpQ+AzFhYWdqxHkClVGYlZ/9pT6yXzHknCUl7b9Y7exVyFSLDEZCLMibUSa05F/XSIzK+pvPM1lBYWSguLhYVzS7q2QhkCn2GnXvGJ9RIXjMdJRILm7t5suaPkbmBW7DqTKbuW6rkVqi6thdLCQmlhkUwm1c7iQWS9WCFX1lkrmou4mVK1YyNQx0tGQKFQOIcyBD4jl9s6s6KUkjO1HD71TVteceN0A6m5vVjtHZQWFkoLi+2uF80o15DPmJk51/epG5JT6RLL+UpjATen6VQNyXqpfw2BSIy53QXPoLSwUFpYzMzMKNdQP7KwuLFIerGi88h8jrmMtiGKR0qYz5bbKgHpF2Rh3e0ueAalhYXSwsJOxBCoGYEnMKSkXDWo6GalLc0wf6/qkophHa8YBpW0Rmkpz0UTQ6RLVZ7cptTjWQdSPXub1hvdBhOlhYXSos7m/T9boQyBCyxkNYpVnWLFMKtrVQ3bC7EiPsJqocoD5eyOcfz9nqJfxEfc7oJnUFpYKC0sxsfHWdzkRWiFcg31mEzJ3KA1l9FYL1YpVewbAbCmvW5v5vICygVgobSwUFpY2HUNKUPgILlydcfcOyuFznLziIjzeYb8itLCQmlhobSwGBmxNztSriGHWC1UeHKlQEAIRmJBwsFzbayUsmNDgOxzf89uUFpYKC0slBYNdN1e/WY1I3CAuUyZ48vmom1Fl5xcL7Vsly5VO3bpyErrcw8iSgsLpYWF0sIin8/baqcMQZtUdIPFnMYPFvM8u1ba4OdfzFXIls+N3+94NoAqzN2M0sJCaWGhtLCYnZ211U4Zgl2Q13TOpEs8Mp/j/jNZnlopbrlz95nV4oYUsIaUjlTnUoW5LZQWFkoLC6WFhd3i9WqNYBsMKcmUqqwVq2aET9W+7zGvGcxnNfaMRAEz5UPVcCDSJ+C9msWuMSBaaPfeR+nPPoZcWELMTBG77RYiN163sdGAaGELpUWDcDhsq50yBJvQdIP12oV/vbRzvv7tOJUuMTEUJhIKOOIWAhDRnbOPDgqDoIV2730U7/4glMzNgXJ+0XwOG4zBIGhhF6WFRSqVsjUr8IxrSAjxUSHEohDikV6/d7PL53s1l4+doi07oRvw7HoJ3ZCNbKCdIotpR87TDwyCFqU/+1jDCFgHy+bxJgZBC7soLSyWl5dttfPSjOCvgD8F/rrbb2RISbpk3vWvFSuUq93bnLWSrxAUzu3yFdGEMyfqA7yghS23TQfIhdYbgjYf94IWXqHftNANyYm1EueP777OQiqVspV0zjOGQEr5L0KIQ906f93ls1askHYwR78dFnPOFXiXelVlUqnhthZ23TadIGamkPPnpggQMxtLlrqthZfoFy3yms79Z+pH2tYAACAASURBVDJ851SGYEDwN2890nJ/0nZommarnWdcQ91krVDh/tOmy2e10Fsj4DjVfk8ktwtc1sKu26YTYrfdArHopoNR83gzalxY+FyLuWyZ/3NskT/8xkm+8uQambJOMhJkMWfvot5MsWivNoNnZgQ7sbi4yK233kooFELXdW666SZuv/125ufnSSQSBINBMpkMU1NTrK6uIqVkamqKhYUFZDiOLJaRWhGRGKvlIhGI+AiysG5uSZcGslJCJMfN8LNAEBFNIotpRDSB1KtQLVuvB0OIyBCymEHEksiqBlXNej0UQYQiyFLOfB+tAHq16fUoIhhClvOIeApZzoGhN14X4RiIAFIrIIZGkcUMICGWxEgvNMrx+f0zaV/5Jtpf/m/k4hJiepLou95K+NoX2vtMho6RXXbvMy20TuYlFxaRVc2sndvh/yn8iqsxyu9C+8jHkUuriKlxIrf+GOHrXmKOg9pnkoaO1CtdHXtiaNSRz9Tt/xPRIYzssq8+kxEb5gfzGb49V+JE1rpTvWQ8wtVTAd501X5y2VVOrFeYnZ21dd1LJpPEYjFb11chPVR/sOYa+pyU8vLNrx09elQePny4rfOu5CscXy501jmPYKQXCPRJYe7NrhUAYlHid91hy7XithaZN97S2m0zO83Ip52bFdjBbS28hJ+0KFR0vncmy7dPZUjXikhFg4Ln7Rvm6gMpJobM8M9rzhshYDOldDMnTpxgZWXl/uuvv/6F27XzzYxAUSPYP/+y7VwrtnzsLmsRu+2WlobsHLdNL+ijcdExPtBiIavxrVNpvj+Xo1LbXzQxFObqAyM8b+8w0ZAzXvtIJGKrnWcUE0L8PfAKYFIIcRr4z1LKv3C3V96jnzIr2o2I2Qq3tagbq25GDdnFbS28hFe1MKTk+FKBfzuV5plVKx/SRRNxXnxeigsn4m3d9W/H8PAwc3NzO7bzjCGQUv6E233wA7KYafgz/Y7diJit8IIWkRuvc+XCvxkvaOEVvKZFscn9U68hHgkKrto7zNUHRphK2Ltrbwc7oaPgIUOgsIeI9c+uyU5dK/2kRacoLSy8osVSTuNbpzI8eDbbcP+MxUMN90883P1UGGNjY/7aR6Cwh6xqfbNhplPXSj9p0SlKCws3tShXDR5fKvDg2SxPrVqhmxeMx3nxeSNcPDnkuPtnO/oufFRRo7r7WGIv05Frpc+06AilhUWPtagakieWCzw8n+P4UqFx9x8OCK7ck+Sa81JMJ7vn/tmOUslebQZlCHyGyrVuobSwUFpY9EIL3ZA8s1bkkfkcjy0WNmQmPpCKcsVskiv2JBnqgftnO2ZnZ5VrqB+RuVWET2Kku43SwkJpYdEtLQwpOZ0u8/B8jmMLefKaVQZydjjC5TNJrphNMBq3l/q5Fzhej0AIMQG8FtgjpfwDIcReICClPN1eFxVtEXJniuk0jiRr6xMtHEFpYeGgFlJK5nMaD8/neGQ+39j0BWbc/+WzCa6YSTLlkutnJ+zuLLZlCIQQ1wKfBL4LvAz4A+Bi4E7g9e11UdEOog++8E4la+sHLZxCaWHhhBbLeY2H5/M8spBjOW8ljRyJBrl8NskVs0n2DEcQPVz4bYd43F4Yrd0ZwR8DPy6l/IoQYq127FvA1W30TdEBspTzfXRIxzuKa/SDFk6htLBoV4t0qcoj8zkens8xl7UWnIfCAY7U3D4HRmM9jfrplLW1tZ0bYd8QHJJSfqX2ez05kbaLv1c4hIiPuN2Fjul0R3GdftDCKZQWFrvRIq/pHFsw3T4n1q0Im2hQcHg6wRWzSS4YjxMM+Ofi38zExISji8WPCiFukFJ+senYq4CH2+mcon2kVvDUrsl2sLujeKd1hK206HaxGC/SD+PCKXbSolQx+MFSnofnczy9WqReSjwUEFwyOcQVs0kunozvOve/F8lms7ba2TUEvwZ8TgjxeSAuhPgfmGsDb2yve4q20as7t/E4dnYU21pHaKFFL4rFeJI+GBeO0UKLim5wvBbr/8RykWrt6h8QcPFEnCtmkzxnOkHMoWRvXsFuYRpbhkBK+W9CiOcCbwc+CpwCrlYRQ72nH+LF7ewotrOO0EoLp9Yf/EY/jAunqGuhG5KnVoo8vJDjB4t5NN28+Avg0FiMy2eTXDadIBFxN9a/mzi6j0AIcaeU8v2Y0ULNx39VSvmH7XVR0Q79Ei++047iLdcR5hfNOgALS4ipcWK3/8xGd5FD6w+7xW13VL+Mi04xpOTZs0scy4Z5dDFPoWJt9No3EuXy2QSXzyQZiQ3G8qbT+wh+G3h/i+P/CVCGoJeEoju36QO2WkcAGsfl4so5bp9OM5q2gyfcUQMyLlohpeRsptwI98yWdcBc+J1KhLliNsnls8lGkZdBwpHwUSFEfRQHhRCvhA01oS8A7K1EKBxD+KDohhO0XEdoxSa3jxvFYrzgjhqUcdHMYmOjV47VorUuMBoNcPmeEa6YTTCT9H6sfzdxqjBNvTBMDHNtoI4E5oFf3HXPFB0hy3nPpNntJq3WEbabIaRf/NqGSyZ+1x09ddO45Y7a8F4DMi7WipXGLt+FpmLuyUiQIzNmuOde1gmOqjUTgHQ6bavdtoZASnk+gBDir6WU73SgX4oOEfGU213oGZvXEbaqEQyAlA2XTPyuO3paM9gNd9Q579XH4yJbrnJswQz3PJ22Zl6xUIDLarH+h8atjV5SG3Wrq55jcnLSucViZQS8gyznEBF7+UP6DVvuIhcihLxQu9hv40JKua3LpljReXQhz8MLOZ5dLTV2sYYDgsPTZqz/hRNDhFps9PKbFt3EkRlBHSHECPAe4Fpgkqa1AinlebvvnqJtDH3nNn3KZncRUrZs10uXDHikdrFPxsVctswnH14kW9bZl4pyIBXjwGiU/SMxhIDjS2as/5MrBWrRngQFXFTb6PWcqSEiO2308okWvaBSqezcCPtRQx8C9gO/A/wN5n6C/4CZiE7RQwY9XrzZXZR5wztbXvR76ZKp43btYj+Mi8eX8vzjw4uNeP6nVoo8tWJW0BJAMCAaG70EZlWvK2YTXDqd2FVZRz9o0SucrkfwGuBSKeWKEEKXUn5aCPFd4LPAH3XQT8UuUfHiFpGfejPlD3zMVZeMV/DyuJBScvRkmi8dX0UCz92T5LoLxzibKXNqvcypdIm5TJmqITmQinL5bJIjMwmGo+1FQnlZi17j9D6CAFB3NuWEEClgDrho911TdIIIK99nneiN1xEYSg1cXqFWeHVc6IbkCz9Y5rtnzEjzV144xrXnjyKEYCwe5siMGelU0Q00XTqyy9erWrhBIpFwdEbwEOb6wFeAb2C6inLA8XY7qGgT0V+5UDpCBFx3ybi9o7iBS+NC0w3OpMucXC+R13SeuyfJ/pR5IS5WdD7x/UWeWi0SCgjefGSKy2dbh7iGgwEcq+qoviMNgkF7oto1BD+LtUD8S8B7gVFARRP1GKkVEPFht7vhCdzWwhM7imv0Sotsucqp9RIn1kucWi8zly03sncCfOtUhoOjMV6wb5hvPLvOUr5CIhLkJ66c4cBob+7U3R4XXiKTydhqt6MhEEIEgZ8Cfg9ASrkIvKuDvik6QAypGOk6bmvhhR3FdbqhhSEly/kKJ9dLjcdacWNmTwHsGY5wXq1gywNns5yoGQqA6USYn3zeLGM9rOPr9rjwElNTU864hqSUuhDi32OGjypcRhYziHDvo2K8iNtaeGFHceM9HdCiohuczZQ5uW66ek6tlyhWjQ1tIkHB/lSM80ajnDcaY38qRrQpdfMrLxzje2eyfOd0hulkmDddNk0s3FtXjdvjwkusrq7aamfXNfTXwLsx1wYUrtI6dn4wcVcLL+wotmhPC0OaqZrvP5Ph+JIVu19nJBrkvNEYB0ZjnDcaYyYZ2bZaVzQU4CUHU7zkoJs7ndV3pI7cYq/NZuwagquBXxRC/DpmLYLG2aWUP7zr3inaRk17LdzWwgs7iuvsVot0qcoDZ7J872yWdMl09whgJmm6ecxHlFQs5LukbW6PCy8xNTXF0tLOM1S7huDPaw+Fy8j8moqRruG2Fp7YUVzDjha6IXliucD9Z7I8sVxo3M2NxUM8f98wV+0Z7os8/W6PCy+xsLBgq53dXEO9y+Cl2BY/1aXtdmilF7RwO3y1znZarBUrfO9MlgfOZmu5+s20DYenE7xg3zDnj8cbCdv6AS+MC6+QTCYd3UegUOwKL4VWDiJVQ/L4Up77T2d5erXYuPufGArzgn3DXLV3uK9LNCp2hzIEPkNqRUR8xO1u7EgvQiv9okUvqGuxnNf43pksD57Nkq+VaQwFBJfNmHf/B0djvvP57xY1LixyuZytdsoQ+AyRGHO7C7boRWilX7ToNhXd4NFslO89cZZn10qN49PJMC/YN8KVe5K7Strmd/ppXNTdq19aWCK2b5pL7no3e2++wfbfz8zMKNdQPyIL64iRabe7sSO9CK30ixbdwJCSuYzGQ3NZvj+Xa8T7hwOCy2eTvGDfMPtT0b6/+29Fv4yLze7V0ukFHrnzfQC2jYGdiCGwX48gilnA/ieACSllSgjxGuASKeWf2nonhUP444vdm9BKf2jhBOWqwel0iZPrZU6tlziVLjXSOQPsSQR4wXnjXDGbJBYa9Fw7/TEuWrlXjWKZ43ffY9sQ2L0RsDsj+CNgH/A24J9qx47VjitD0EP84vvsRWhlsxZORii5nUhOSslKocLptJmi+fR6mYWcds42qbF4iIsmhnj+vmH2xEGEoz3ro5dx+zvi1PjZyo1aOrNFudYWjI+Ps7i4c3u7huDNwEVSyrwQwgCQUp4RQuyz3SOFI8jCum9ipLsdWlnXwskIJbeinRZzGj9YynNqvczpdIlCZWNqh4CAPcPRRmqH80ZjG/L1G+kF34yLbuPmd8TJ8bOVezW2z77by1HXEKBtbiuEmAJ2XoVQOIqIDLndBc9Q18LJCKVeJpJbK1Z4ZN4syr6Q0za8lowE2Z+KcmA0xv5UlL0j0W1LNKpxYeGmFk6On1bu1UA8yiV3vdv2OUZGRhxdLP4E8DEhxK8ACCH2AH8MfNx2jxTOII2d2wwKNS2cjFDqdrRTrlzlkYU8j8znOJW2vuDxUIBLpxNcMBFnfyrK6G5TO6hxYeGiFk6On83u1XaihnTdXv1mu4bgPwK/DzwMDAFPYKac+B3bPVI4gqyUEFgJvdz2Z7tJXQsnI5S6Ee1UrOg8tpjn4fk8zzRt7goHBIenzaLsF04MEdommdtObB4Xg4ybWjg9furu1WvOG2lr93c+n7fVzm6KCQ34FeBXai6hZWk3rZ3CUZoLcw/67t26Fk5GKDl1Lk03OL5U4OH5HE8sW1k9gwIumjQv/s+ZGtrW3bMbVMF2Cze18FIiQnC4eL0Q4p3Ag1LK70spl2rHrgSeK6X8nx31VLErmgtze6kwihvUtXAyQqmTc1UNyVMrBR6ez/P4Ur4R3imAC8bjXD6b4LLpRFc2d6mC7RZuauGlRITgfPH6/wpctenYKeAzgDIEvSRgXUS8VBjFFZq0cCJCqeFmm1+EQAB2Meldymn85f1z5DXLJ7s/FeWK2SRHZhIbIny6QmBwdg7viMtaeCURIUA4bK8ynN3ROQJsLn6ZxqxbrOghImoV//ZWYZTe06xFp2x2s2HUFqJtuNuklHz5ydWGEbj+ojGumE32tjyjg1r4HaWFRSqVsjUrsOugfBS4edOxNwOP7bJfig6RxXTj99htt0Bs0yYiF/2RvaZZi05p6WZrvGi627biu2eyPL5UIBIU3PHSA/zw+WM9NQLgrBZ+R2lhsby8bKud3RnBbwBfEEL8OPAUcBFwPfDatnqnaBsRTTR+95o/stc0a9Fp9NRO7rTm1yu6QalqPtLFKp97zPyyveHSKSYSvTUAdZq1GHSUFhapVMrRfQT/ClwO/CRwAPg28EtSylNt91DRFlKvbsik4iV/ZK+pa9FJ9JQhJevFKnJygtDS1ndPudExPvz1E5SqBlXj3LWD0ViIK/a455LYPC4GGaWFhaZpOzfChiEQQgSBHDAqpXxfh/1SdEp1C/fFIFLTwm70VKlqsJjTmM+WWchqLOTMh6ZLnnPt63jNp/+OcKVyzttUwmG+fv3ryWlWda9YKEAsHKz9DPCCfcPd+5x2UOPCQmnRoFgs2mq3oyGQUupCiOPABHC2w34pOkTFi1vUtdjKrWMsLPGVJ1fNC35WY71WpH0zw5Eg+vXXcmJyiEOf/ATBpWWkCCCkgTY5iX7r23nVa17Jj9Qu+uGA8Fx6ZzUuLJQWFo7uIwD+FvicEOIDwGmwEiFKKe9rq4eKtlDx4hZ1LbaKnsqOjPIvz6w3nocCgqlEmJnhCDPJCLPJKDPDEatk4/PfAD/9BgCeWilwJlPm5YdGfVHPV40LC6WFhdP7CG6r/XzPpuMSuMDmORROEFS1hBrUtGi1m7MSDvPtf/cmfuj8UWaT5oV/fChM0GYahwsnhrhwwkeJ3NS4sFBaNIhEIrba2U0xcX5HvVE4hsoyaVHXInLjdegS8n/6l4RWVsimRvnGq97A1e/4ES6aHAy91LiwUFpYDA8PMzc3t2M726ZTCBECXopZoOY0cFRK2drp2gZCiBuBDwBB4CNqYbo1sphBROJud8MT1LXIlat8OHkh6V/+L43Xrj4wMjBGANS4aEZpYWFnfQDs5xo6DHwWiGOmljgAlIQQr5dSdryprBaZ9N+BV2Mame8IIT4jpXy003P3GyKmdk3WOVmOcPTBeZ5eLW4o25iMBHnVRYO1YKjGhYXSwmJsbMzRxeIPAR8G3l/POiqEuLN2/JXtdrKJq4EnpZRP1879ceCNmDuaFU3IqjYwG2aqhuRLx1c4sVZifCjMVDLMdCLCVDLC2XSZzzy2htGU1bNuC1598TjRAavbO0jjYieUFhaOhY/WuAp49abU038M/NYu+7UV+zBnGnVOA9c0N1hcXOTWW28lFAqh6zo33XQTt99+O/Pz8yQSCYLBIJlMhqmpKVZXV5FSMjU1xcLCAjIcRxbLSK2ISIwhC+uAQMRHzLJ2kSGQhpnHPDmOzK1CIIiIJpHFNCKaQOpVqJat14MhRGTInIbGksiqBlXNej0UQYQiyFLOfB+tAHq16fUoIhhClvOIeApZzoGhN14X4RiIAFIrIIZGkcUM2le+ifbRf0QurSCmJ4m+662Er32hrz8TSPP3/FpjOi+1IvnwCP/w0AKncmbOn/mcBi1Kr14zG+GlB8cwShk+8FCR0WiAK4bySD3muc/Uzf+TzK0iY8m++kzt/p+kXsUw9L76TPl8kGwmQ6VSYXZ21tZ1L5lMsra2ZusCLOyUFRBCPALc0RwqKoR4JfCnUsojtt5p+/P/KHCjlPJdtefvAK6RUv5Cvc3Ro0fl4cOH2zr/Sr7C8eVCp910lXOSogHEosTvuqPvdhYv5jT+9oF51ktVUrEgrzs8SalisJivsJTXWMpplKsG154/wjUHLRfQerFCIhIk7FCOfz8h9Qoi6E56C6/Rj1q0W5imXC5z7Nix+6+//voXbtduNxXKPiOE+BxwAjgIvA54+6571pozmOsOdfbXjilq9HPtgYpucCptFm0/ky43fP77RqL8xFUzW6ZwNtILG56P9jjRm5dQsfMWSgsLR/cRSCk/I4R4PvBjwF7gEeC3pZTH2+7hRr4DXCyEOB/TALwVM6+Roka/1h4oVQ3+4ttnWMxvTO1w+UyCNx2Z2v7uPmQvRnogUFpYKC0axGIxW+3sRg1dJaV8EPjdTjq1FVLKqhDiF4AvYoaPflRKeawb7+VX7NYecKuGsZ33regGD83lCArB/lSUiUSYzz22xGK+QioW5DlTCfaPRNmfitnK4inUF76B0sJCaWERj9sLo7XrGvqSEGIJ+Hvgb6WUz7Tbsa2QUn4B+ILT5+0X7NRCdauGsZ33PZ0u8aljSyw33flHg4KyLokEBe98/h4mE7v7AstSTkWH1FBaWCgtLOwuFttdVdsD/DpwGHhICHFUCPGLQojpNvun2CWRG68jftcd5gxACMTs9DkLxdutI3STLd/3Q39Frlzln59c5SPfPstyvsJkIsxl0wlGokHKtXjP1x2e3LURABDxESe63xcoLSyUFhYTExO22tldI9CBzwOfF0LEMWP8bwPeD0S3+9tBoRcumciN1xF6+ZUEkq3/uW6tI2yX/fO//ctJwCzg/tKDKa67cKzh90+XqpSqBjPJ9qbyUiuoHaQ1lBYWSguLbDZrq92usjMJIWLAjwA/DrwQ+Maue9aH9NQlo2+d1cONGsaFik55YoJoi5J42dExhsIBxofC3HDJBOeNbly4SsVCpDp58220GDiUFhZKiwZ2C9PYcg0JIV4rhPgbzC09vwZ8HbhQSvmqtnvYR/TSJbNdrvVe1jDOlat86YkV/ugbJ/nnV7yOSnjT4m4sysyvvIvfeMUhfvbqfecYASdQeectlBYWSguL2dlZW+3szgjej7lQ/Dwp5VPtdqpf6aVLZrsY6V7UMNYNyb+eSPO1p9caJRur111L+YIxIn/9dz2NVlLx4hZKCwulhYXT+wgu66g3fU5PXTKh7ZdkulnDeC5b5tPHlpjLmtPN50wN8cPnj7I/FYMX7IGbb+jK+27JDloMFEoLC6VFg47DR4UQvyWl/L3a77+zVTsp5W/vund9hp3QTqcQXSq6UTUkT60UWC9VCQhBvX5LQTPIazqZcpXHFvMY0izU/vrLJrnI5cIt3dLCjygtLJQWFk4Uptnf9PuBLdrsnKhoAOiFS6aOLOd3lWZXSkm2rDMSO/dfLaXkVLrMQ3NZjs3nKVaNbc8lgGsOjHD9Rd7I7rlbLfoZpYWF0sIinU7barelIZBS3tb0+0870Ke+ppsumWZEPGU7VFVKySceXuTYQp5XXzzOyw+NAmYSvofms3x/Lsda0YqwmElGOJCKIgFDSqSEoUiQRCRIMhJkz7BZ49criHhHMUd9hdLCQmlhMTk56Vw9AiHEZcAPAePAKvANVTTGHcpf+CLlP/rLlqGq4RvM0hCilqXw6Mk0xxbyAHz5iVWy5Sqn02VOpy0X1nA0yHNnkzx3T5LZYX/5VmU5h4g4H43kR5QWFkoLi45nBADCvKL8BXALZo2As5i1A/YKIf4n8DPSTh5rhWNof/GJlqGqxQ/9FX8/dSl5TectV0yzXKjw5SdWATgyk+DYQp5/O5kBIBIUXDad4Mo9wxwaj7WV3tYTGLrbPfAOSgsLpUWDSqWycyN2nhH8HPAK4MVSyu/UDwohXoQZTvrzwD3tdVHRDnJptfXxhSWeXjWrEX3422capRtfejDFDZdM8I1n1jmTKXFkOslzpoeIOJSz360kd6DixZtRWlgoLSxmZ2dtuYZ2uhq8A7MgzXeaD9ae/3LtdUUvmWo9yLOpMZKRIJdMDqHpEoFZsvE1F5vtf+j8Ud565SxX7Ek6agSKd3/QDJ2VsuGm0u69b+c/dgCZa20UBxGlhYXSwsLuPoKdrgiXYe4ibsXXa68resBSTuMzjy7xT9f+yDm7eCvhMN997Zt4+/Nn+YmrZnjzkSlufdFeXn5otLFe0A3cSnJXR4SVH7iO0sJCaWGRSNjLwrqTaygopWyZtUhKmRVCuB9D2MdIKXlmtcS/nljniZVaEeorrwbgZV/6DMPpNQpjE5R++m28/i03EqoF/1+1d7g3/XO7WI4afhZKCwulRYNgMGir3U6GIFyrTbzVbaXaudEFqobkkfkcR0+kzaLtQCgguGpvkhePVUm+4i2ceOfriQ6F2dtm5k4ncCPJXTNSKyDivTF6XkdpYaG0sMhkMrba7XQhXwQ+usPrCocoVHS+ezrDt09myGpm5EMyEuTqAyO8cP8IiUgQWSkjwkEOT7tfeKOXO6pbIYZGe/I+fkBpYaG0sJiamup8H4GU8pBTHVK0RkrJXFbjgbNZHjiTpVJL5DadDPPS80a5fDaxoW6vLGYQ4d7cce9EL3dUt8JLWriN0sJCaWGxumpv4Vy5dlzAkJLT6TKPLuR5bDHPesna3XvhRJyXnpfiwon4Fgu93tq20asd1a05Vws3w1k7ofN+e2tcuIvSoo7dbV7KEPSQdKnK0RNpHp7PkdOsTS/JSJBLpxO8aP/Ijikc1LTXYrMWbtVs7hQn+q3GhYXSwmJqaoqlpZ2DN5Qh6AEr+Qr/99l1HprLUtvnxWgsxKXTCS6bSbA/FbW9u1fm11Su9RqbtdgunNXLhsCJfqtxYaG0sFhYWLDVThmCLpItV7nvyTUeOJtFYoZeHZlJ8NKDKfaNRNuK8fdCLdZuul92c+7NWrgeztomTvTbC+PCKygtLJLJpHNJ5xS7Q9MN/vXZNN88sY6mSwICnrdnmJcdSjGZ8E72znbopvul03O7Hc7aLn7tt6J/UDsvOqRqSMpVg1LVoFQxePBslj/55im++vQami45PDXE7S/ZzxuPTDliBKRWdKDX7dPN3cS7PfdmLXpZs9lJnOi32+PCSygtLHK5nK12akawS4oVnZPrJZ5dK3FircRctozRYmF+73CEGy6Z4NC4s9NUkRhz9Hy7pZvul92ee7MWboeztosT/XZ7XHgJpYXFzMyMcg05QU7TOblWbFz4F3LahuA0gZnWGUAISEZCXHv+KFfsSXYlvbMsrCNGph0/r1266cbY7blbaeFuOGv7dNpvt8eFl1BaWNiJGAJlCM4hU6pyYq3Es2tFTqyXWMpvzOcdFLAvFePgWIxDYzEOpGI9Ltvobu2Abu4m3v25fVpHoSsoLSyUFnXsBqQMtCGQUrJeqtbu9s27/ubSjQDhgGD/aJRDo3EOjsXYn4pu2Onba0R8xLX3hu66X3Z7bre18BJKCwulhcX4+DiLiztnAhooQyClZLlQqd3xmxf/THljNaNoUHBgNMahMfPCv3ck2sjq6QVkYd31GOluul92c24vaOEVlBYWSgsL5RqqMZ8t85UnurTPDwAAIABJREFU1/jOqQwn1kvktY0X/ng4wMHRuqsnzkwyQtBDF/7NiMiQ213wDEoLC6WFhdLCYmRkRC0WAzw0l+Nj9881nicjQQ6O1S78o3GmkmF/1eyVhts98A5KCwulhYXSooGu26vf3PeG4Ll7krz8UIqxeJhDYzEmhsJdrdrVbWSlhCC1Yzu/Jl/bDXa1GASUFhZKC4t8Pm+rXd8bgj3DUW5/yQGOLxfc7ooj2CnM7dfka7tFFSm3UFpYKC0snCper/AYdgpzu11LuFeoIuUWSgsLpYWF3eL1fT8j6DsCO9cg9WvytV1jQ4uBQWlh0UdaBANw/ni87XXMcDhsq52aEfgMEU3u3GaLnbj9lsTMjhaDgtLCol+0iIUDHJlJMtVBjrJUyt5aiTIEPkMW0zu28Wvytd1iR4tBQWlh0Q9ajMVDXDGbJBHpbHazvLxsq51yDfkMEd25aL1fk6/tFjtaDApKCws/ayEEHEhF2ZeKOXK+VCql9hH0I1Kv2sqk0rxDtx5KWnzP+/vKKNjVYhDoRIt+CzX267gIBQQXT8YZjdvz69tB0zR77+3YOyp6Q7W8c5sm+jqUdJda9DVtatGX48OH4yIRCXLJ1BAxhxNYFov2ajOoNQKfsdsY6X4OJVXx4hbtatGP48Nv42I6Geby2YTjRgDMfQR2UIbAZ+w2RrqfQ0lVvLhFu1r04/jwy7gICLhwIs6FE0NdS3Njdx+BMgR+I7g7b15fh5LuUou+pk0t+nJ8+GBcREOCIzMJppPdrWEeidg7vzIEPmO3mRX7OZRUZZm0aFeLfhwfXh8Xo7XQ0GS0+wZreHjYVjvvm07FBmQxg4jYr4PsRCipV6NKdqtFP9OuFv0YauzlcbEvFeVAKtqzxJd2QkdBGQLfIWK73zXZSSEZL0eVtKNFv9KJFn6t87wVXhwXoYDgwok440POhYbaYWxsTCWd60dk1V5csFN4Oaqk11p4GaWFhde0SEQCXD6b6LkRAPvho2pG4Dd6PMg9HVXisS+8qygtLDykxWQizAXjcdeqHpZKJVvt1IzAZ/QqRlq79z4yb7wFpGzdjzaiSurnTL/4tWTeeAvavfd11Ee/xYt3Ez9r0Y/jIiDg0HiMiyeHXC19a3cfgZoR+AyZW+16Ye7N6wLn0EZUSTfWGnqhhV/wqxb9Mi7CQUEiEiQRDjIUCZCMhrqyQWy3qHoE/Uqou3HHsMW6QA0xO91WVMl2aw1tL1T2QAvf4FMt/DYuhIB4KMBQJEgiEmQobP4eCbp/0W9FLGYveZ3rhkAI8RbgPcClwNVSyu+62yNvI3rwhd/S/y8EI59ub5G4G2sNvdDCL/hVCy+Pi1BAMBQJ1C745oU/Hg50bRdwN4jH7YXRum4IgEeAm4D/4XZH/IAs5bqeZlfMTCHnF1se99I5e6GFX3BLi4CAYEAQFIKqIakardeUtsIr4yIWDpAIB0lEAgyFgwxFgkQ94NrplLW1NVvtXDcEUsrHgJ5tsPA7Ij7S9feI3XbLuWsEHe427cY5e6GFX+hUi4AwI1zCwQBBAYHaxT0oBIEA5u8BYV74hai9vvF7W9B0HlnIoRv237fX4yIYwLzQ1+7wh2oXfjcXdLvJxMSEqkfgB3a7a1dqha7vmuzGbtNunLMXWviFTrRIRoNcMB7vuBrWUCTIJZND/GCpsFWw2Tl0c1xEQ6Jxd1/358fD/VPP2A7ZbNZWu54YAiHEPwOt4ph+S0r5aTvnWFxc5NZbbyUUCqHrOjfddBO333478/PzJBIJgsEgmUyGqakpVldXkVIyNTXFwsICMhxHFstIrYhIjCEL64BAxEeQhXUzN4k0kJUSIjluZi8MBBHRJLKYRkQTSL0K1bL1ejCEiAyZ29ljSXMTS1WzXg9FEKGIOU2NjyC1AujVptejVO47Sun/vwfKZtyznF+k+N4PYhTSRG+8DkTAHNRDo8hiBpBIvYqRXmh86bv1mcKvvIbQDz1vw2cy8ms7fiYRDCHLeUQ8hSznwNAbr4d/+AWEr33Rhs9kZBbN3/Nru/9M+XUMKbv+f9ruM4lwrOX/qe3P1ObYk/l1ZHxkV58JLc/e6SnC1RzLcyuEZmdtfZ+SSXPnbi6XY2ZmhqWlJYQQjI+Pk15aYioUZyFTsv2ZQi85QvLlf7jhMxn5Ndv/J3KrRGNx4rGI+X8KVhkJ5dCrVWYnzc8kEwlKwSCLbXympaUlRkZG0HWdfD7PbE2ncDhMKpVieXmZVCqFpmkUi8XG65FIhOHhYVZWVhgbG6NYLFIqlRqvx2Ix4vE4a2trTExMkM1m0TSt8Xo8HicSiZBOp5mcnCSdTlOpVBqv2/k/pdP2ynYKadd0dxkhxNeAO7daLD569Kg8fPhwW+deyVc4vlzooHfdIfPGW1r7R2ent1yUlXoFEez9DkUvorSw2K0WIzFzFtCtO+RnVovMZ53f2LU5THMobC7gNruoyuUy0Wh0m7MMDuVymWPHjt1//fXXv3C7dso15CLtREz4NV68GygtLOxqEQoIzhuNMTPc3SijQ2MxMqUqhcouFgya6CRMc35+noMHD7b1vv2Gb/YRCCHeDPwJMAV8XgjxoJTyBpe71RU2rweIkWFkOnNOu20jJkLqTqeB0sLChhZj8RAXjMeJOBwNc/aTX+T43fdQOrNIbN80l9z1bvbefAMHx2I8tmh/Jj6dDDMcDXUcpmk3ZHIQ8E34qJTyU8Cn3O5Ht2m1g5JQEMIhqFSthjtETAgfFN3oFUoLi+20CAcFh8ZiTCacnwWc/eQXeeTO92EUzXFdOr3AI3e+D4C9N9/A+FCI1UJ1u1MAZs3eCyecqSNgtxjLIKAK03iMljsoqzrE44jZaRACMTtN/K47to8aKue73FP/oLSw2EqLyUSYK/cku2IEAI7ffU/DCNQximWO330PAOeNxrATmbk/5dzszu4C6SBgVwt1S9UjtvT7Z3OMfPl/2T6PiKcc6pH/UVpYbNYiEhRcMB5nrMupj0tnzg12aD4eDwfZMxzlTGaLvFWYswEnUzRPTk46di6/Mzk5qeoReAmnasPKcs6J7vQFSguLZi1mhyNctXe460YAILZvesfj+1JRwsGtpwVOzgZAzQiasauFMgQ9wrHasIbuXKf8jtLCwtCJhQMcmUlwfg/z319y17sJxDeO60A8yiV3vbvxPFiLVGqF07MBgEql4uj5/IxdLZRrqEc4tYPSC7nWvYLSwkQI2DM7y6GpZM8Tou292QzwaxU11Mx0MsJCTiNX3mi8nZ4NgP0c/IPA7OysSjHhNZyoDati5y2UFmYZxAsnhlieO01AuJN7ae/NN5xz4W/FobEYj8xbi9rdmA2A2kfQjN19BMo15DNE2F5+8UFgkLWIhgTnj8e4YjZp7rRNeD8L63A0xGTCuvB3YzYA+EKLXmFXCzUj8BtC2e4GfaJFNCQYqW2kKlUNcppOQdNpldE5GhLsG4kxlQxvcAMFg/5IpnZwNMZasUIs1J3ZAPhHi15gVwtlCLrMbrOL7oTUCoj4sIM99C9+1SIeDjASDTESCzIcDbXMe29ISbFikCvr5LQqpYrBZCJyjgGok8lkGBsb60X3OyISCrBvJNrVLKB+0aIXZDLnZi5ohTIEXaQb9VjF0Khj/fM7ftBCCDP//UgsyEg0xHA0SNhGvpyAqCVXiwSZYefNYFNT7Rdy6TV7RqJdXdT2kxbdZmpqSi0Wu0036rHKYgYRVgMdvKlFQEAyEmQ4FmIkat7x9yKUc3V1laEhZ1I0dJtuRzb5SYtus7q6aqudMgRdpBv1WMEbacO9gbe0GB8KcfHkkCs1bb2STt4LKC0s7GrRH6ttHsWp3cQb/tYH7pBe4TUtQgHhWmFz5Q6xUFpY2NVCGYIu4thu4iZk3l4x6kFAaWGxsLDgdhc8g9LCwq4WyjXURbpRj1XV6LVQWljUSy0qlBbNJJNJtVjsBZzYTaxwh1g4QKnNClsKhZ9QriGfIbWi213wDDtpYSNKc1sOjcWIhXc+Safv4wS5nMrEWkdpYWFXCw8MYcVuEIn/196dB8lxlncc/z7d0zPdc+4xs4fWkiwj2wIb28HmKipQWKFsICmCCSnIxaFUYccpQhWERKGKEKqCSaUgBSTBqSQUhLMg5shpYa4iEBMI4bJxcAFCkS2ttKtjL+2hXb35o2f2nd2dme1dr7a7d55Plcqemd6Zd34rzTP9vm+/r14o09ApC99zuHmkzDXVPGV/cxcvuSJcU82v+0HvuU7HZZa3w+Bgd6+51EyzsKJmoYUgZcyF83E3ITE6ZXFVfSnm/oLHdYNFbhwuMlTKbvjbeyHrcmXv+mMRxWy8yxqMjT2RKck7i2ZhRc1CC0HqxPvNM1laZ1EteFT8lcNf+azLvr6Am0fKXNUXUMhG/6s/UMwyUOy8Lk4h5kIgMU1bTSLNwoqahRaClJEgnqWGk6hdFsVc+w9l1xEGS1luGC5x3WCBasGLtKfuvr6g44d93GcEfX26N0ODZmFFzUILQcpo15DVLotcxP6fsh9eCfy0kRJ7enz8Fou/NTgiXFPLk2lTNQodis920O4QS7OwtGtoh5KsrqHS0C6LVqt5duK5DiOVHDftKnKglm/7zd/POOzvbz1ekHWdSIvJXS7lsp4pNmgWVtQstBCkjdF57QDlnNs2i40WggYRoTfvsavcfrXP3rzHSJsNVeLsHlpa0v2bGzQLK2oWWghSxlyci7sJscrXN2i/bqjIQO4SuczKrhrXoW33TVTFXOfrLHdXcmsGoyHeQjAzM7P+QV1Cs7CiZqGFIGV22obtUWfbOAJ7enI8dbhIuf4hvHtkmNKqD+2o4wOd+BmHbIfrAkSE/dVgzTHZTZ6JbAXdsN3SLKyoWWghSBkzHW198TRwHRju0A3TUPEz3DBcZKTir1jdc3R0lGDVlb9b9WG8usCslnUdrq7mScpMxaiblHcDzcKKmoWuNZQ2zs7Zj7WQdVt2sTR4rrC316dWaF0sPM9b8cHvOltzRgBQijALqOxn2NvjMzq9sCWv+UR43uXZ/zeNNAsrahZ6RpAykts5KyuWchmyrkO+xXo+tYLHjcPFtkUAoFKprNj7tuC5mx4oXq3TtQjNhss5+i/TJuwbUalU4m5CYmgWVtQstBCkjJmdiLsJW6ZUHx8oN50VZBzh2lqe/dX8utMxx8fHV8z9z2fdNYPHm1XIupG3mNzdZhbRdhofH4+7CYmhWVhRs9BCkDKSK8TdhC1TqheARvdQ3nO4fqhAX8Rv2JVKBdeR5QXfClmX7BZ1DTkia8Yf2knCkgb6LdjSLKyoWegYQcqYpcXIqw0t3P+lLd0UZysFnrM8zbPsZ6gWvOWF4qJaWAj75oOMwyWzhJ9xOl4dvFFxbTu5GY0slGbRLGoWWgjSZnE+0mEL93+J2XveC3Ph8Wb0dHgbElEMmgdjM45wdXXjV0zPzob7EfiegwFEiH056Lg0slCaRbOoWWjXUMpEvY5g7v0fWi4C9s758P4EWG96ZhSNOdJ+xqWQdcm5TiK6aeKgc+ctzcLS6wh2qKjXEZhTrRebanf/5VLIOi0HcKNMz1xPY4504DkUsm7Xng2Azp1vpllYeh3BTuW2/pWtHg+QcgkzMbnmOBmsRX6pzezZ67lCxc/QE2So+OH00Im5RX54ambFMc3TPjcrmw2nlvoZh0vGdO3ZANgslGbRLGoWWghSptWKm63GA8i44GXg4qI90M/h3/WqSK9TyLocqOX5zokpLpn1j/c9h709fssZPxU/Q3/e48yFi8DWrclTKpWWX7vbNbJQmkWzUqnEyZMn1z1O/wWljJld+y2/5XjA4hIEATI0ACLI0ADB4ddHGih2BPb3B2QzTqSLpQLP4cbhYsdpn3t7/eVtIrdifADgzJkz9fZKqmb4XA6NLJRm0SxqFnpGkDLir72yuG2//9Q05Qc+ueHXuKLik69/ax8sZRmbudi+PQJP6g/W/SDOZRx2lXMcPz+/JeMDAL297Tev7zaahaVZWL29vZGKgZ4RpIxZXDsvuF2//0bGAxpKOXfFevylXKbjCqFDpWzkb/i7yrnlgd2toNMELc3C0iwsnT66U7UoBP5drwJ/1TIHGxgPaPBc4Un9wZpB16FS6wEn33PYXfEjP78j4fIRG7lorJO5ue7em6GZZmFpFlbULLQQpEyr6wiyt99KcPj1mxoPaBgoety0q9RyNk9/3mu52cuTNnglMLAls4UadL64pVlYmoUVNQsdI0gZM30WqQyuuT97+62bumI47zns6wtWLPy2musItaLHycnwbMRzhZFyruPPbIfR0VH27t0baxuSQrOwNAtLryPYqTLrzwv2XGHxksF0mPbpCFxRyTFczkWacTNYzDI5t8hQKUe14CVilo7vR++W2uk0C0uzsKJmoYUgZSRCISjnMrgOnJ6+iOuwPFunoSfIcGWvv6FumsBzuWE4WfOzgyCIuwmJoVlYmoUVNQsdI0gZMze97jGB57CnxyfjCFf2BlxR8dnTk8NzhaurAU8eKKwpAifuO8JXbnkp9w8/h6/c8lJO3Hfkcr2FLXPu3Lm4m5AYmoWlWVhRs9AzgpSRoLzuMXnPxXMdDgzkl6d2jlR8hkq5loO7J+47wkNveieXZsOzhrnHTvHQm94JwK6X3baFrd9a/f39cTchMTQLS7Ow+vv79TqCncgsXFj3mMaGKqvn97eb4fPoPfcuF4GGS7PzPHrPvZts5faYmpqKuwmJoVlYmoUVNQstBGmztNjxYZGNr70z9/jpDd2fFLoBiaVZWJqFFTULLQQps95+BH7G2fCMHn9kYEP3J4XOF7c0C0uzsHQ/gh1qvf0I8pu4YOuaw3fiBCuvTHaCHNccvnPDz7WddN15S7OwNAtLryPYBpvZE9hzhb7A49T0Jk9fM7mWd/sZh7nFS5E3XG/WGBB+9J57mXv8NP7IANccvjPRA8Wg0wSbaRaWZmFFzSL2QiAifw78ErAA/AR4jTHmfLytWl+7PYFLuQzzz39u258bKGaXp3Y+Phlt/+EGzxUKxYAZR7i4ZK8WGynnGChl+f7JqU2dEUBYDJL+wb+abkBiaRaWZmFFzSIJXUMPANcbY24AHgUOx9yeSNrtCTz5vg+0/VYuEl6hC7Cn12dPz/pX/bkOVAseB2p5njZSIm9mGS7Zs4LeIMPunhx+xmFvT7CpM4K0mpiYiLsJiaFZWJqFFTWL2M8IjDGfb7r5DeBX4mrLRrTbA2DuxGn29wc8dGpmzRIPPX6GXMZ+UI9UcmQc4ei52RXHOhLu6lUtePQG3oppn9VqFT/IcnJqnowjXF3NL68WOljKYjqtK7HDVKvVuJuQGJqFpVlY1Wo1ldcRvBb497gbEUW7tf79kQGKuQxXVNb25TfOBlbcV8qyvz/AESj7Llf1BTxtpMSBgQLVQnbN3P+JiQlcR9jT47dc0rmb9u3Vb36WZmFpFlaizghE5AtAq3lMbzHGfK5+zFuAReCjrZ7j9OnTHDp0iEwmw9LSEnfccQd33303o6OjFAoFXNdlcnKSWq3G2bNnMcZQq9U4deoUxgsws/OYhVmk0Iu5cB4QJChjLpwP9wE2lzAX55BiXzgzx3GRXBEzO4HkCpilRVicX348+5qXMf/uD8C87R4SP8u+3/9tjh07Ri6Xw78kXJiaQIIy7uIsk2PnyQ8NMTo6ShAEZLNZJiYmqFarjLjTLM0t0tMzxInHjrd9TwsLCxw7doxisciFeTg9Pc3g4CBjY2OICH19fYyNjVEul1laWmJmZoah+mt6nkelUmF8fJxKpcLCwgKzs7PLj2ezWUqlEmfOnKG3t5fZ2Vnm5uaWH/d9nyAIOHfuHP39/UxNTbGwsLD8+Or3NDExwcWLF5cfX+/3VCyGu69NR3xP4+PjADvqPW329zQ+Pk5/f/+Oek+b/T0tLCxw4sSJHfWeNvt7mpxcu7Vty8/oJHQliMirgdcBB40xLS+dffDBB82BAwc29fxnZi7y6Pj6V+RuVPOsoVYzbWYvLvGD0WmWLsGenhwjG9jEpZ35+XlyudYzh7qNZmFpFpZmYc3Pz/Pwww9/++DBg7d0Oi72MQIRuR14M/C8dkUgqRp7AOzrC9fxWS3wXPb0+Bw7N0etRbfQZuha65ZmYWkWlmZhRb2OIAljBH8JlIAHROS7IpLsBW5WyThCrdD+Q36olGNfX0DW3ZqoC4XCljzPTqBZWJqFpVlYUbOI/YzAGLM/7jZsRsYR+vMeA0Vv3e0aB7bobADAdbduq8e00ywszcLSLKyoWSThjCA1HAn37722lufmK0pc1R9QzG1vLY06+NMNNAtLs7A0CytqFrGfEaRBOedSLWTpL7TexH071Wqtp612I83C0iwszcKq1WqRriPQQtBG4DnUCh79hSx+JjknTmfPniWfz8fdjETQLCzNwtIsrLNnOy9S2aCFoInnCtWCRzXvbXuXT1RJmO6bFJqFpVlYmoUVNYtkftptI9eB3sCjWvDo8TOJvzJXT3stzcLSLCzNwqrVaoyNtV4Op1ly+jy2kQj0BBn2VwNuHilzdTVPb+AlvggAnDp1Ku4mJIZmYWkWlmZhRc2iq84IClmHaiFLNe+RTVC//0Y0LoVXmkUzzcLSLKxisaiDxQ35rMONw0XyWZ1frJRSq6Xza/EGBZ67Y4rA9PR03E1IDM3C0iwszcKKmkVXFIKdZHBwMO4mJIZmYWkWlmZhRc1CC0HKRJkB0C00C0uzsDQLK2oWWghSJg0zm7aLZmFpFpZmYUXNQgtByvT19cXdhMTQLCzNwtIsrKhZaCFIGT3ttTQLS7OwNAtLu4Z2qHK5HHcTEkOzsDQLS7OwomahhSBllpaW4m5CYmgWlmZhaRZW1Cy0EKTMzMxM3E1IDM3C0iwszcKKmoUWgpQZGhqKuwmJoVlYmoWlWVhRs9BCkDJRN6PuBpqFpVlYmoWVps3r1QZ89rOfjbsJiaFZWJqFpVlYUbPQQpAyn/70p+NuQmJoFpZmYWkWVtQstBCkzOLiYtxNSAzNwtIsLM3CipqFpGVbty9+8YtjwLG42xG3s2fPVvv6+sbjbkcSaBaWZmFpFlY9i8LBgwc7btuWmkKglFLq8tCuIaWU6nJaCJRSqstpIUgZEXm5iDwsIpdE5Ja42xMHEbldRH4kIj8WkT+Muz1xEpEPiMhpEXko7rbETUR2i8iXReSH9X8jvxd3m+IiIr6IfFNEvlfP4k86Ha+FIH0eAu4Avhp3Q+IgIi7wV8ALgacArxSRp8Tbqlh9ELg97kYkxCLwRmPMU4BnAXd38d+NeeBWY8yNwE3A7SLyrHYHayFIGWPMI8aYH8Xdjhg9A/ixMeanxpgF4BPAS2JuU2yMMV8FzsbdjiQwxpw0xvxP/f+ngEeAkXhbFQ8TamxY7NX/tJ0ZpIVApc0IcLzp9mN06T921Z6IXAn8HPBf8bYkPiLiish3gdPAA8aYtllktq9ZKioR+QLQarWotxhjPrfd7VEqTUSkCNwHvMEYMxl3e+JijFkCbhKRHuAzInK9MablWJIWggQyxvxC3G1IsMeB3U23r6jfpxQi4hEWgY8aY3StCcAYc15Evkw4ltSyEGjXkEqbbwFXi8g+EckCrwD+KeY2qQSQcKf2vwceMca8O+72xElEavUzAUQkAF4A/G+747UQpIyIvFREHgOeDfyriByJu03byRizCPwucIRwMPCTxpiH421VfETk48CDwLUi8piIHIq7TTF6DvCbwK0i8t36nxfF3aiYDANfFpHvE355esAY8y/tDtYlJpRSqsvpGYFSSnU5LQRKKdXltBAopVSX00KglFJdTguBUkp1OS0ESq0iIr8uIp+Pux1KbRedPqpSQUR+BuwCdhljxpvu/w7h6or7jDE/i6d18aivp3MU8OrXVyi1KXpGoNLkKPDKxg0ReSqQ3+yTiciaJVZa3ReX+pLbSl12WghUmnwY+K2m268C/qH5ABF5sYh8R0QmReS4iLyt6bErRcSIyCER+T/gSyLyahH5uoj8hYicAd5Wv+9rTT/3nvpzTYrIt0Xk55seC0TkQyJyTkQeEZE316/8bjy+S0TuE5ExETkqIq9v9+ZE5IMi8n4R+TcRmQGe3+n9YPekOC8i0yLy7PrzvLbelnMickRE9kaPWHUjLQQqTb4BlEXkyfVvy68APrLqmBnCYtEDvBi4S0R+edUxzwOeDNxWv/1M4KfAIPCnLV73W4TdT33Ax4BPiYhff+yPgSuBqwjXc/mNxg+JiAP8M/A9wqWyDwJvEJHbaO/X6m0oAV9b5/08t/7fHmNM0RjzoIi8BPgjws2LasB/AB/v8HpKaSFQqdM4K3gB4VpDK1YeNcZ8xRjzA2PMJWPM9wk/BJ+36jneZoyZMcbM1m+fMMa8zxiz2HRf83N+xBhzpv74u4AccG394V8F3mGMOWeMeQx4b9OPPh2oGWPeboxZMMb8FPhbwgLWzueMMV+vt38u4vtpdidwT30Do0XgHYRLEetZgWorMf2hSkX0YcIukX2s6hYCEJFnAu8ErgeyhB/an1p12PF1bq9+zjcBhwgHqw1QBqr1h3et+vnm/98L7BKR8033uYTf0ttZ0ZaI76fZXuA9IvKu5qchPCM51uHnVBfTMwKVKsaYY4SDxi8CWq03/zHCZal3G2MqwL2EH4Qrnmad28vq4wFvJvzm32uM6QEmmp7zJOGeCA3NeyUcB44aY3qa/pSMMZ1WxFzdlk7vp1W7jwOvW/WagTHmPzu8pupyWghUGh0i3Jh7psVjJeCsMWZORJ5B2Of+RJQIN0UfAzIi8lbCM4KGTwKHRaRXREYIl8hu+CYwJSJ/UB9UdkXkehF5+gZfv937GQMuEY5PNNxbb891ACJSEZGXb+D1VBfSQqBSxxjzE2PMf7d5+HeAt4vIFPBWwg/qJ+IIcD/wKGHXyhwru2/eTrhv8lHgC8A/AvP1di4Bv0g40HwUGAdwjfrVAAAAn0lEQVT+Dqhs4PXbvh9jzAXCgeWvi8h5EXmWMeYzwJ8BnxCRScIdqV64wfesuoxeUKbUFhKRu4BXGGM6DegqlSh6RqDUEyAiwyLyHBFxRORa4I3AZ+Jul1IbobOGlHpissDfEM5iOg98AvjrWFuk1AZp15BSSnU57RpSSqkup4VAKaW6nBYCpZTqcloIlFKqy2khUEqpLqeFQCmlutz/A7fs1RSEqTkFAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "hpdi_pred = hpdi(predictions_1, 0.9)\n", "\n", "ax = plot_regression(dset.MarriageScaled.values, mean_pred, hpdi_pred)\n", "ax.set(xlabel=\"Marriage rate\", ylabel=\"Divorce rate\", title=\"Predictions with 90% CI\");" ] }, { "cell_type": "markdown", "metadata": { "id": "b5i71NCFN7mE" }, "source": [ "We have used the same `plot_regression` function as earlier. We notice that our CI for the predictive distribution is much broader as compared to the last plot due to the additional noise introduced by the `sigma` parameter. Most data points lie well within the 90% CI, which indicates a good fit.\n", "\n", "#### Posterior Predictive Density\n", "\n", "Likewise, making use of effect-handlers and `vmap`, we can also compute the log likelihood for this model given the dataset, and the log posterior predictive density [[6](#References)] which is given by \n", "$$ log \\prod_{i=1}^{n} \\int p(y_i | \\theta) p_{post}(\\theta) d\\theta \n", "\\approx \\sum_{i=1}^n log \\frac{\\sum_s p(\\theta^{s})}{S} \\\\\n", "= \\sum_{i=1}^n (log \\sum_s p(\\theta^{s}) - log(S))\n", "$$.\n", "\n", "Here, $i$ indexes the observed data points $y$ and $s$ indexes the posterior samples over the latent parameters $\\theta$. If the posterior predictive density for a model has a comparatively high value, it indicates that the observed data-points have higher probability under the given model." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "id": "ZpNwpvk_N7mE" }, "outputs": [], "source": [ "def log_likelihood(rng_key, params, model, *args, **kwargs):\n", " model = handlers.condition(model, params)\n", " model_trace = handlers.trace(model).get_trace(*args, **kwargs)\n", " obs_node = model_trace[\"obs\"]\n", " return obs_node[\"fn\"].log_prob(obs_node[\"value\"])\n", "\n", "\n", "def log_pred_density(rng_key, params, model, *args, **kwargs):\n", " n = list(params.values())[0].shape[0]\n", " log_lk_fn = vmap(\n", " lambda rng_key, params: log_likelihood(rng_key, params, model, *args, **kwargs)\n", " )\n", " log_lk_vals = log_lk_fn(random.split(rng_key, n), params)\n", " return (logsumexp(log_lk_vals, 0) - jnp.log(n)).sum()" ] }, { "cell_type": "markdown", "metadata": { "id": "dXu_hzcDN7mE" }, "source": [ "Note that NumPyro provides the [log_likelihood](http://num.pyro.ai/en/latest/utilities.html#log-likelihood) utility function that can be used directly for computing `log likelihood` as in the first function for any general model. In this tutorial, we would like to emphasize that there is nothing magical about such utility functions, and you can roll out your own inference utilities using NumPyro's effect handling stack." ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "dZxKq_ETN7mF", "outputId": "9574a5f7-56aa-404a-e491-f7dc2a1c6636" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Log posterior predictive density: -66.70008087158203\n" ] } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "print(\n", " \"Log posterior predictive density: {}\".format(\n", " log_pred_density(\n", " rng_key_,\n", " samples_1,\n", " model,\n", " marriage=dset.MarriageScaled.values,\n", " divorce=dset.DivorceScaled.values,\n", " )\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "wbxnyQazN7mF" }, "source": [ "### Model 2: Predictor - Median Age of Marriage\n", "\n", "We will now model the divorce rate as a function of the median age of marriage. The computations are mostly a reproduction of what we did for Model 1. Notice the following:\n", "\n", " - Divorce rate is inversely related to the age of marriage. Hence states where the median age of marriage is low will likely have a higher divorce rate.\n", " - We get a higher log likelihood as compared to Model 2, indicating that median age of marriage is likely a much better predictor of divorce rate. " ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ZBdf-6NEN7mF", "outputId": "128e3a0b-1742-44a3-f3d1-43b0cc4c5eef" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sample: 100%|██████████| 3000/3000 [00:04<00:00, 722.23it/s, 7 steps of size 7.58e-01. acc. prob=0.92]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " mean std median 5.0% 95.0% n_eff r_hat\n", " a -0.00 0.10 -0.00 -0.17 0.16 1942.82 1.00\n", " bA -0.57 0.12 -0.57 -0.75 -0.38 1995.70 1.00\n", " sigma 0.82 0.08 0.82 0.69 0.96 1865.82 1.00\n", "\n", "Number of divergences: 0\n" ] } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "\n", "mcmc.run(rng_key_, age=dset.AgeScaled.values, divorce=dset.DivorceScaled.values)\n", "mcmc.print_summary()\n", "samples_2 = mcmc.get_samples()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 405 }, "id": "6udy6d7_N7mG", "outputId": "28a2e4af-81be-4229-b944-1af4d64ddd98" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "posterior_mu = (\n", " jnp.expand_dims(samples_2[\"a\"], -1)\n", " + jnp.expand_dims(samples_2[\"bA\"], -1) * dset.AgeScaled.values\n", ")\n", "mean_mu = jnp.mean(posterior_mu, axis=0)\n", "hpdi_mu = hpdi(posterior_mu, 0.9)\n", "ax = plot_regression(dset.AgeScaled.values, mean_mu, hpdi_mu)\n", "ax.set(\n", " xlabel=\"Median marriage age\",\n", " ylabel=\"Divorce rate\",\n", " title=\"Regression line with 90% CI\",\n", ");" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 405 }, "id": "DYGHPBueN7mG", "outputId": "7646a234-b1ee-44f2-8510-02b76654d582" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "predictions_2 = Predictive(model, samples_2)(rng_key_, age=dset.AgeScaled.values)[\"obs\"]\n", "\n", "mean_pred = jnp.mean(predictions_2, axis=0)\n", "hpdi_pred = hpdi(predictions_2, 0.9)\n", "\n", "ax = plot_regression(dset.AgeScaled.values, mean_pred, hpdi_pred)\n", "ax.set(xlabel=\"Median Age\", ylabel=\"Divorce rate\", title=\"Predictions with 90% CI\");" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "FbKMD13UN7mH", "outputId": "b271e24a-b880-4e2c-97e9-15ea3a671610" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Log posterior predictive density: -59.251956939697266\n" ] } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "print(\n", " \"Log posterior predictive density: {}\".format(\n", " log_pred_density(\n", " rng_key_,\n", " samples_2,\n", " model,\n", " age=dset.AgeScaled.values,\n", " divorce=dset.DivorceScaled.values,\n", " )\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "xVss4FJNN7mH" }, "source": [ "### Model 3: Predictor - Marriage Rate and Median Age of Marriage\n", "\n", "Finally, we will also model divorce rate as depending on both marriage rate as well as the median age of marriage. Note that the model's posterior predictive density is similar to Model 2 which likely indicates that the marginal information from marriage rate in predicting divorce rate is low when the median age of marriage is already known." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "18Qm4F2_N7mH", "outputId": "2ce7fc1d-48bb-4c7f-bad6-f0b929f3ac6b" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sample: 100%|██████████| 3000/3000 [00:04<00:00, 644.48it/s, 7 steps of size 4.65e-01. acc. prob=0.94]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " mean std median 5.0% 95.0% n_eff r_hat\n", " a 0.00 0.10 0.00 -0.17 0.16 2007.41 1.00\n", " bA -0.61 0.16 -0.61 -0.89 -0.37 1225.02 1.00\n", " bM -0.07 0.16 -0.07 -0.34 0.19 1275.37 1.00\n", " sigma 0.83 0.08 0.82 0.69 0.96 1820.77 1.00\n", "\n", "Number of divergences: 0\n" ] } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "\n", "mcmc.run(\n", " rng_key_,\n", " marriage=dset.MarriageScaled.values,\n", " age=dset.AgeScaled.values,\n", " divorce=dset.DivorceScaled.values,\n", ")\n", "mcmc.print_summary()\n", "samples_3 = mcmc.get_samples()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "XfW5xgpwN7mI", "outputId": "0561ac6d-ae08-4f60-a5a2-13c81f13ce3f" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Log posterior predictive density: -59.06374740600586\n" ] } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "print(\n", " \"Log posterior predictive density: {}\".format(\n", " log_pred_density(\n", " rng_key_,\n", " samples_3,\n", " model,\n", " marriage=dset.MarriageScaled.values,\n", " age=dset.AgeScaled.values,\n", " divorce=dset.DivorceScaled.values,\n", " )\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "nptmx2OaN7mI" }, "source": [ "### Divorce Rate Residuals by State\n", "\n", "The regression plots above shows that the observed divorce rates for many states differs considerably from the mean regression line. To dig deeper into how the last model (Model 3) under-predicts or over-predicts for each of the states, we will plot the posterior predictive and residuals (`Observed divorce rate - Predicted divorce rate`) for each of the states." ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 948 }, "id": "3vEDRtFON7mI", "outputId": "a11368d2-222d-484d-9529-10ae11cc042a" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "# Predictions for Model 3.\n", "rng_key, rng_key_ = random.split(rng_key)\n", "predictions_3 = Predictive(model, samples_3)(\n", " rng_key_, marriage=dset.MarriageScaled.values, age=dset.AgeScaled.values\n", ")[\"obs\"]\n", "y = jnp.arange(50)\n", "\n", "\n", "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(12, 16))\n", "pred_mean = jnp.mean(predictions_3, axis=0)\n", "pred_hpdi = hpdi(predictions_3, 0.9)\n", "residuals_3 = dset.DivorceScaled.values - predictions_3\n", "residuals_mean = jnp.mean(residuals_3, axis=0)\n", "residuals_hpdi = hpdi(residuals_3, 0.9)\n", "idx = jnp.argsort(residuals_mean)\n", "\n", "# Plot posterior predictive\n", "ax[0].plot(jnp.zeros(50), y, \"--\")\n", "ax[0].errorbar(\n", " pred_mean[idx],\n", " y,\n", " xerr=pred_hpdi[1, idx] - pred_mean[idx],\n", " marker=\"o\",\n", " ms=5,\n", " mew=4,\n", " ls=\"none\",\n", " alpha=0.8,\n", ")\n", "ax[0].plot(dset.DivorceScaled.values[idx], y, marker=\"o\", ls=\"none\", color=\"gray\")\n", "ax[0].set(\n", " xlabel=\"Posterior Predictive (red) vs. Actuals (gray)\",\n", " ylabel=\"State\",\n", " title=\"Posterior Predictive with 90% CI\",\n", ")\n", "ax[0].set_yticks(y)\n", "ax[0].set_yticklabels(dset.Loc.values[idx], fontsize=10)\n", "\n", "# Plot residuals\n", "residuals_3 = dset.DivorceScaled.values - predictions_3\n", "residuals_mean = jnp.mean(residuals_3, axis=0)\n", "residuals_hpdi = hpdi(residuals_3, 0.9)\n", "err = residuals_hpdi[1] - residuals_mean\n", "\n", "ax[1].plot(jnp.zeros(50), y, \"--\")\n", "ax[1].errorbar(\n", " residuals_mean[idx], y, xerr=err[idx], marker=\"o\", ms=5, mew=4, ls=\"none\", alpha=0.8\n", ")\n", "ax[1].set(xlabel=\"Residuals\", ylabel=\"State\", title=\"Residuals with 90% CI\")\n", "ax[1].set_yticks(y)\n", "ax[1].set_yticklabels(dset.Loc.values[idx], fontsize=10);" ] }, { "cell_type": "markdown", "metadata": { "id": "_gtKVD5jN7mJ" }, "source": [ "The plot on the left shows the mean predictions with 90% CI for each of the states using Model 3. The gray markers indicate the actual observed divorce rates. The right plot shows the residuals for each of the states, and both these plots are sorted by the residuals, i.e. at the bottom, we are looking at states where the model predictions are higher than the observed rates, whereas at the top, the reverse is true.\n", "\n", "Overall, the model fit seems good because most observed data points like within a 90% CI around the mean predictions. However, notice how the model over-predicts by a large margin for states like Idaho (bottom left), and on the other end under-predicts for states like Maine (top right). This is likely indicative of other factors that we are missing out in our model that affect divorce rate across different states. Even ignoring other socio-political variables, one such factor that we have not yet modeled is the measurement noise given by `Divorce SE` in the dataset. We will explore this in the next section." ] }, { "cell_type": "markdown", "metadata": { "id": "ZB2I6FAhN7mJ" }, "source": [ "## Regression Model with Measurement Error\n", "\n", "Note that in our previous models, each data point influences the regression line equally. Is this well justified? We will build on the previous model to incorporate measurement error given by `Divorce SE` variable in the dataset. Incorporating measurement noise will be useful in ensuring that observations that have higher confidence (i.e. lower measurement noise) have a greater impact on the regression line. On the other hand, this will also help us better model outliers with high measurement errors. For more details on modeling errors due to measurement noise, refer to Chapter 14 of [[1](#References)].\n", "\n", "To do this, we will reuse Model 3, with the only change that the final observed value has a measurement error given by `divorce_sd` (notice that this has to be standardized since the `divorce` variable itself has been standardized to mean 0 and std 1)." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "id": "ue9-HyWuN7mJ" }, "outputs": [], "source": [ "def model_se(marriage, age, divorce_sd, divorce=None):\n", " a = numpyro.sample(\"a\", dist.Normal(0.0, 0.2))\n", " bM = numpyro.sample(\"bM\", dist.Normal(0.0, 0.5))\n", " M = bM * marriage\n", " bA = numpyro.sample(\"bA\", dist.Normal(0.0, 0.5))\n", " A = bA * age\n", " sigma = numpyro.sample(\"sigma\", dist.Exponential(1.0))\n", " mu = a + M + A\n", " divorce_rate = numpyro.sample(\"divorce_rate\", dist.Normal(mu, sigma))\n", " numpyro.sample(\"obs\", dist.Normal(divorce_rate, divorce_sd), obs=divorce)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "id": "BFm91doZN7mJ" }, "outputs": [], "source": [ "# Standardize\n", "dset[\"DivorceScaledSD\"] = dset[\"Divorce SE\"] / jnp.std(dset.Divorce.values)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "twtxSbBpN7mJ", "outputId": "1eb4cd42-3b0d-4ae8-bb65-335b6faf205a" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "sample: 100%|██████████| 4000/4000 [00:06<00:00, 578.19it/s, 15 steps of size 2.58e-01. acc. prob=0.93]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", " mean std median 5.0% 95.0% n_eff r_hat\n", " a -0.06 0.10 -0.06 -0.20 0.11 3203.01 1.00\n", " bA -0.61 0.16 -0.61 -0.87 -0.35 2156.51 1.00\n", " bM 0.06 0.17 0.06 -0.21 0.33 1943.15 1.00\n", " divorce_rate[0] 1.16 0.36 1.15 0.53 1.72 2488.98 1.00\n", " divorce_rate[1] 0.69 0.55 0.68 -0.15 1.65 4832.63 1.00\n", " divorce_rate[2] 0.42 0.34 0.42 -0.16 0.96 4419.13 1.00\n", " divorce_rate[3] 1.41 0.46 1.40 0.63 2.11 4782.86 1.00\n", " divorce_rate[4] -0.90 0.13 -0.90 -1.12 -0.71 4269.33 1.00\n", " divorce_rate[5] 0.65 0.39 0.65 0.01 1.31 4139.51 1.00\n", " divorce_rate[6] -1.36 0.35 -1.36 -1.96 -0.82 5180.21 1.00\n", " divorce_rate[7] -0.33 0.49 -0.33 -1.15 0.45 4089.39 1.00\n", " divorce_rate[8] -1.88 0.59 -1.88 -2.89 -0.93 3305.68 1.00\n", " divorce_rate[9] -0.62 0.17 -0.61 -0.90 -0.34 4936.95 1.00\n", "divorce_rate[10] 0.76 0.29 0.76 0.28 1.24 3627.89 1.00\n", "divorce_rate[11] -0.55 0.50 -0.55 -1.38 0.26 3822.80 1.00\n", "divorce_rate[12] 0.20 0.53 0.20 -0.74 0.99 1476.70 1.00\n", "divorce_rate[13] -0.86 0.23 -0.87 -1.24 -0.48 5333.10 1.00\n", "divorce_rate[14] 0.55 0.30 0.55 0.09 1.05 5533.56 1.00\n", "divorce_rate[15] 0.28 0.38 0.28 -0.35 0.92 5179.68 1.00\n", "divorce_rate[16] 0.49 0.43 0.49 -0.23 1.16 5134.56 1.00\n", "divorce_rate[17] 1.25 0.35 1.24 0.69 1.84 4571.21 1.00\n", "divorce_rate[18] 0.42 0.38 0.41 -0.15 1.10 4946.86 1.00\n", "divorce_rate[19] 0.38 0.55 0.36 -0.50 1.29 2145.11 1.00\n", "divorce_rate[20] -0.56 0.34 -0.56 -1.12 -0.02 5219.59 1.00\n", "divorce_rate[21] -1.11 0.27 -1.11 -1.53 -0.65 3778.88 1.00\n", "divorce_rate[22] -0.28 0.26 -0.28 -0.71 0.13 5751.65 1.00\n", "divorce_rate[23] -0.99 0.30 -0.99 -1.46 -0.49 4385.57 1.00\n", "divorce_rate[24] 0.43 0.41 0.42 -0.26 1.08 3868.84 1.00\n", "divorce_rate[25] -0.03 0.32 -0.03 -0.57 0.48 5927.41 1.00\n", "divorce_rate[26] -0.01 0.49 -0.01 -0.79 0.81 4581.29 1.00\n", "divorce_rate[27] -0.16 0.39 -0.15 -0.79 0.49 4522.45 1.00\n", "divorce_rate[28] -0.27 0.50 -0.29 -1.08 0.53 3824.97 1.00\n", "divorce_rate[29] -1.79 0.24 -1.78 -2.18 -1.39 5134.14 1.00\n", "divorce_rate[30] 0.17 0.42 0.16 -0.55 0.82 5978.21 1.00\n", "divorce_rate[31] -1.66 0.16 -1.66 -1.93 -1.41 5976.18 1.00\n", "divorce_rate[32] 0.12 0.25 0.12 -0.27 0.52 5759.99 1.00\n", "divorce_rate[33] -0.04 0.52 -0.04 -0.91 0.82 2926.68 1.00\n", "divorce_rate[34] -0.13 0.22 -0.13 -0.50 0.23 4390.05 1.00\n", "divorce_rate[35] 1.27 0.43 1.27 0.53 1.94 4659.54 1.00\n", "divorce_rate[36] 0.22 0.36 0.22 -0.36 0.84 3758.16 1.00\n", "divorce_rate[37] -1.02 0.23 -1.02 -1.38 -0.64 5954.84 1.00\n", "divorce_rate[38] -0.93 0.54 -0.94 -1.84 -0.06 3289.66 1.00\n", "divorce_rate[39] -0.67 0.33 -0.67 -1.18 -0.09 4787.55 1.00\n", "divorce_rate[40] 0.25 0.55 0.24 -0.67 1.16 4526.98 1.00\n", "divorce_rate[41] 0.73 0.34 0.73 0.17 1.29 4237.28 1.00\n", "divorce_rate[42] 0.20 0.18 0.20 -0.10 0.48 5156.91 1.00\n", "divorce_rate[43] 0.81 0.43 0.81 0.14 1.50 2067.24 1.00\n", "divorce_rate[44] -0.42 0.51 -0.43 -1.23 0.45 3844.29 1.00\n", "divorce_rate[45] -0.39 0.25 -0.39 -0.78 0.04 4611.94 1.00\n", "divorce_rate[46] 0.13 0.31 0.13 -0.36 0.64 5879.70 1.00\n", "divorce_rate[47] 0.56 0.47 0.56 -0.15 1.37 4319.38 1.00\n", "divorce_rate[48] -0.63 0.28 -0.63 -1.11 -0.18 5820.05 1.00\n", "divorce_rate[49] 0.86 0.59 0.88 -0.10 1.79 2460.53 1.00\n", " sigma 0.58 0.11 0.57 0.40 0.76 735.02 1.00\n", "\n", "Number of divergences: 0\n" ] } ], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "\n", "kernel = NUTS(model_se, target_accept_prob=0.9)\n", "mcmc = MCMC(kernel, num_warmup=1000, num_samples=3000)\n", "mcmc.run(\n", " rng_key_,\n", " marriage=dset.MarriageScaled.values,\n", " age=dset.AgeScaled.values,\n", " divorce_sd=dset.DivorceScaledSD.values,\n", " divorce=dset.DivorceScaled.values,\n", ")\n", "mcmc.print_summary()\n", "samples_4 = mcmc.get_samples()" ] }, { "cell_type": "markdown", "metadata": { "id": "puqL7TzPN7mJ" }, "source": [ "### Effect of Incorporating Measurement Noise on Residuals\n", "\n", "Notice that our values for the regression coefficients is very similar to Model 3. However, introducing measurement noise allows us to more closely match our predictive distribution to the observed values. We can see this if we plot the residuals as earlier. " ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "id": "XKnLI7__N7mJ" }, "outputs": [], "source": [ "rng_key, rng_key_ = random.split(rng_key)\n", "predictions_4 = Predictive(model_se, samples_4)(\n", " rng_key_,\n", " marriage=dset.MarriageScaled.values,\n", " age=dset.AgeScaled.values,\n", " divorce_sd=dset.DivorceScaledSD.values,\n", ")[\"obs\"]" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 993 }, "id": "a7aC5dgdN7mJ", "outputId": "e6878a39-dbb8-485c-bd56-79a66155f8a5" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "sd = dset.DivorceScaledSD.values\n", "residuals_4 = dset.DivorceScaled.values - predictions_4\n", "residuals_mean = jnp.mean(residuals_4, axis=0)\n", "residuals_hpdi = hpdi(residuals_4, 0.9)\n", "err = residuals_hpdi[1] - residuals_mean\n", "idx = jnp.argsort(residuals_mean)\n", "y = jnp.arange(50)\n", "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(6, 16))\n", "\n", "\n", "# Plot Residuals\n", "ax.plot(jnp.zeros(50), y, \"--\")\n", "ax.errorbar(\n", " residuals_mean[idx], y, xerr=err[idx], marker=\"o\", ms=5, mew=4, ls=\"none\", alpha=0.8\n", ")\n", "\n", "# Plot SD\n", "ax.errorbar(residuals_mean[idx], y, xerr=sd[idx], ls=\"none\", color=\"orange\", alpha=0.9)\n", "\n", "# Plot earlier mean residual\n", "ax.plot(\n", " jnp.mean(dset.DivorceScaled.values - predictions_3, 0)[idx],\n", " y,\n", " ls=\"none\",\n", " marker=\"o\",\n", " ms=6,\n", " color=\"black\",\n", " alpha=0.6,\n", ")\n", "\n", "ax.set(xlabel=\"Residuals\", ylabel=\"State\", title=\"Residuals with 90% CI\")\n", "ax.set_yticks(y)\n", "ax.set_yticklabels(dset.Loc.values[idx], fontsize=10)\n", "ax.text(\n", " -2.8,\n", " -7,\n", " \"Residuals (with error-bars) from current model (in red). \"\n", " \"Black marker \\nshows residuals from the previous model (Model 3). \"\n", " \"Measurement \\nerror is indicated by orange bar.\",\n", ");" ] }, { "cell_type": "markdown", "metadata": { "id": "05vX0drHN7mK" }, "source": [ "The plot above shows the residuals for each of the states, along with the measurement noise given by inner error bar. The gray dots are the mean residuals from our earlier Model 3. Notice how having an additional degree of freedom to model the measurement noise has shrunk the residuals. In particular, for Idaho and Maine, our predictions are now much closer to the observed values after incorporating measurement noise in the model.\n", "\n", "To better see how measurement noise affects the movement of the regression line, let us plot the residuals with respect to the measurement noise." ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 405 }, "id": "lmvXOBAsN7mK", "outputId": "12aba4b5-d974-4887-8be1-b223f73d0ad0" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light", "tags": [] }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(10, 6))\n", "x = dset.DivorceScaledSD.values\n", "y1 = jnp.mean(residuals_3, 0)\n", "y2 = jnp.mean(residuals_4, 0)\n", "ax.plot(x, y1, ls=\"none\", marker=\"o\")\n", "ax.plot(x, y2, ls=\"none\", marker=\"o\")\n", "for i, (j, k) in enumerate(zip(y1, y2)):\n", " ax.plot([x[i], x[i]], [j, k], \"--\", color=\"gray\")\n", "\n", "ax.set(\n", " xlabel=\"Measurement Noise\",\n", " ylabel=\"Residual\",\n", " title=\"Mean residuals (Model 4: red, Model 3: blue)\",\n", ");" ] }, { "cell_type": "markdown", "metadata": { "id": "YzFlMShkN7mL" }, "source": [ "The plot above shows what has happend in more detail - the regression line itself has moved to ensure a better fit for observations with low measurement noise (left of the plot) where the residuals have shrunk very close to 0. That is to say that data points with low measurement error have a concomitantly higher contribution in determining the regression line. On the other hand, for states with high measurement error (right of the plot), incorporating measurement noise allows us to move our posterior distribution mass closer to the observations resulting in a shrinkage of residuals as well." ] }, { "cell_type": "markdown", "metadata": { "id": "1NmiOj_fN7mL" }, "source": [ "## References\n", "\n", "1. McElreath, R. (2016). Statistical Rethinking: A Bayesian Course with Examples in R and Stan CRC Press.\n", "2. Stan Development Team. [Stan User's Guide](https://mc-stan.org/docs/2_19/stan-users-guide/index.html)\n", "3. Goodman, N.D., and StuhlMueller, A. (2014). [The Design and Implementation of Probabilistic Programming Languages](http://dippl.org/)\n", "4. Pyro Development Team. [Poutine: A Guide to Programming with Effect Handlers in Pyro](http://pyro.ai/examples/effect_handlers.html)\n", "5. Hoffman, M.D., Gelman, A. (2011). The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo.\n", "6. Betancourt, M. (2017). A Conceptual Introduction to Hamiltonian Monte Carlo.\n", "7. JAX Development Team (2018). [Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more](https://github.com/google/jax)\n", "8. Gelman, A., Hwang, J., and Vehtari A. [Understanding predictive information criteria for Bayesian models](https://arxiv.org/pdf/1307.5928.pdf)" ] } ], "metadata": { "colab": { "name": "bayesian_regression.ipynb", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 0 }