March 2019
Beginner to intermediate
448 pages
13h 14m
English
Content preview from R Statistics Cookbook
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How to do it...
We will use the same house prices example that we used in the previous recipes for linear regression. We have a price variable, and several regressors, such as the number of bedrooms, bathrooms, and so on:
- We first run our example, but with 5,000 iterations and different priors. Let's use a Gaussian prior on each beta coefficient and a lower boundary equal to 0:
library(rstan)library(coda)library(DrBats)data = read.csv("/Users/admin/Documents/R_book/chapter3/house_prices.csv")model ="data {real y[125];real x[125,6];}parameters {real <lower=0> beta[6];real sigma;real alpha;}model {beta ~ normal(5,20);for (n in 1:125)y[n] ~ normal(alpha + beta[1]*x[n,1] + beta[2]*x[n,2] + beta[3]*x[n,3] + beta[4]*x[n,4] + beta[5]*x[n,5] ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.