A multi-variable Bayesian linear regression model using an exponential-normal prior for the coefficients.
data(attitude) design <- as.matrix(attitude[, 2:7])
int <- normal(0, 10) sd <- cauchy(0, 3, truncation = c(0, Inf)) tau <- exponential(0.5, dim = ncol(design)) coefs <- normal(0, tau) mu <- int + design %*% coefs distribution(attitude$rating) <- normal(mu, sd)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.