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loo (version 0.1.2)

loo_and_waic: Approximate LOO-CV and WAIC for Bayesian models

Description

This function is deprecated. Please use loo or waic instead.

Usage

loo_and_waic(log_lik, ...)

loo_and_waic_diff(loo1, loo2)

Arguments

log_lik
an $S$ by $N$ matrix, where $S$ is the size of the posterior sample (the number of simulations) and $N$ is the number of data points. Typically (but not restricted to be) the object returned by extract_log_lik
...
optional arguments to pass to psislw. Possible arguments and their defaults are: [object Object],[object Object],[object Object],[object Object],[object Object]

We recommend using the default values for the

Value

  • a named list with class 'loo'.

    Returned for both LOO and WAIC are the expected log pointwise predictive density (elpd), the estimated effective number of parameters (p), and the information criteria on the deviance scale (e.g. looic = -2*elpd_loo). Also returned are the pointwise contributions of each of these measures, standard errors, and the estimated shape parameter $k$ for the Pareto fit to the importance ratios for each leave-one-out distribution.