rstanarm (version 2.15.3)

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

# S3 method for stanreg
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

# NOT RUN {
 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))
# }
# NOT RUN {
# }