Reporting Bayesian Model Comparison

Automatically report the results of Bayesian model comparison using the loo package.

Usage

# S3 method for class 'compare.loo'
report(x, index = c("ELPD", "IC"), ...)

Arguments

x

An object of class brms::loo_compare.

index

type if index to report - expected log pointwise predictive density (ELPD) or information criteria (IC).

...

Additional arguments (not used for now).

Value

Objects of class report_text().

Details

The rule of thumb is that the models are "very similar" if |elpd_diff| (the absolute value of elpd_diff) is less than 4 (Sivula, Magnusson and Vehtari, 2020). If superior to 4, then one can use the SE to obtain a standardized difference (Z-diff) and interpret it as such, assuming that the difference is normally distributed.

Examples

# \donttest{
library(brms)

m1 <- brms::brm(mpg ~ qsec, data = mtcars)
#> Compiling Stan program...
#> Error in .fun(model_code = .x1): Boost not found; call install.packages('BH')
m2 <- brms::brm(mpg ~ qsec + drat, data = mtcars)
#> Compiling Stan program...
#> Error in .fun(model_code = .x1): Boost not found; call install.packages('BH')

x <- brms::loo_compare(brms::add_criterion(m1, "loo"),
  brms::add_criterion(m2, "loo"),
  model_names = c("m1", "m2")
)
#> Error in eval(expr, envir, enclos): object 'm1' not found
report(x)
#> Error in eval(expr, envir, enclos): object 'x' not found
# }