bayes_R2.stanreg: Compute a Bayesian version of R-squared or LOO-adjusted...

Description Usage Arguments Value References Examples

View source: R/bayes_R2.R

Description

Compute a Bayesian version of R-squared or LOO-adjusted R-squared for regression models.

Usage

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## S3 method for class 'stanreg'
bayes_R2(object, ..., re.form = NULL)

## S3 method for class 'stanreg'
loo_R2(object, ...)

Arguments

object

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

...

Currently ignored.

re.form

For models with group-level terms, re.form is passed to posterior_linpred if specified.

Value

A vector of R-squared values with length equal to the posterior sample size (the posterior distribution of R-squared).

References

Andrew Gelman, Ben Goodrich, Jonah Gabry, and Aki Vehtari (2018). R-squared for Bayesian regression models. The American Statistician, to appear. DOI: 10.1080/00031305.2018.1549100. (Journal, Preprint, Notebook)

Examples

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fit <- stan_glm(mpg ~ wt + cyl, data = mtcars, QR = TRUE, chains = 2)
rsq <- bayes_R2(fit)
print(median(rsq))
hist(rsq)

loo_rsq <- loo_R2(fit)
print(median(loo_rsq))

# multilevel binomial model
if (!exists("example_model")) example(example_model)
print(example_model)
median(bayes_R2(example_model))
median(bayes_R2(example_model, re.form = NA)) # exclude group-level

rstanarm documentation built on Oct. 4, 2019, 1:04 a.m.