# bayes_R2.stanreg: Compute a Bayesian version of R-squared or LOO-adjusted... In rstanarm: Bayesian Applied Regression Modeling via Stan

## Description

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

## Usage

 ```1 2 3 4 5``` ```## 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```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.