waic: Widely Applicable Information Criteria

In surveil: Time Series Models for Disease Surveillance

Widely Applicable Information Criteria

Description

Widely Application Information Criteria (WAIC) for model comparison

Usage

waic(fit, pointwise = FALSE, digits = 2)

Arguments

fit	An surveil object
pointwise	Logical (defaults to FALSE); if pointwise = TRUE, a vector of values for each observation will be returned.
digits	Round results to this many digits.

Value

A vector of length 3 with WAIC, a rough measure of the effective number of parameters estimated by the model Eff_pars, and log predictive density Lpd. If pointwise = TRUE, results are returned in a data.frame.

Source

Watanabe, S. (2010). Asymptotic equivalence of Bayes cross validation and widely application information criterion in singular learning theory. Journal of Machine Learning Research 11, 3571-3594.

Examples

data(msa)
austin_w <- subset(msa, grepl("Austin", MSA) & Race == "White")
fit <- stan_rw(austin_w, time = Year)
waic(fit)
 

surveil documentation built on Sept. 12, 2024, 7:23 a.m.