rstanarm (version 2.13.1)

log_lik.stanreg: Pointwise log-likelihood matrix

Description

For models fit using MCMC only, the log_lik method returns the $S$ by $N$ pointwise log-likelihood matrix, where $S$ is the size of the posterior sample and $N$ is the number of data points.

Usage

"log_lik"(object, newdata = NULL, offset = NULL, ...)

Arguments

object

A fitted model object returned by one of the rstanarm modeling functions. See stanreg-objects.

newdata

An optional data frame of new data (e.g. holdout data) to use when evaluating the log-likelihood. See the description of newdata for posterior_predict.

offset

A vector of offsets. Only required if newdata is specified and an offset was specified when fitting the model.

...

Currently ignored.

Value

An $S$ by $N$ matrix, where $S$ is the size of the posterior sample and $N$ is the number of data points.

Examples

 roaches$roach100 <- roaches$roach1 / 100
 fit <- stan_glm(
    y ~ roach100 + treatment + senior,
    offset = log(exposure2),
    data = roaches,
    family = poisson(link = "log"),
    prior = normal(0, 2.5),
    prior_intercept = normal(0, 10),
    iter = 500 # to speed up example
 )
 ll <- log_lik(fit)
 dim(ll)
 all.equal(ncol(ll), nobs(fit))

 # using newdata argument
 nd <- roaches[1:2, ]
 nd$treatment[1:2] <- c(0, 1)
 ll2 <- log_lik(fit, newdata = nd, offset = c(0, 0))
 head(ll2)
 dim(ll2)
 all.equal(ncol(ll2), nrow(nd))