Generic function and default method for Bayesian version of R-squared for regression models. A generic for LOO-adjusted R-squared is also provided. See the bayes_R2.stanreg() method in the rstanarm package for an example of defining a method.

bayes_R2(object, ...) # S3 method for default bayes_R2(object, y, ...) loo_R2(object, ...)

object | The object to use. |
---|---|

... | Arguments passed to methods. See the methods in the rstanarm package for examples. |

y | For the default method, a vector of |

`bayes_R2()`

and `loo_R2()`

methods should return a vector of
length equal to the posterior sample size.

The default `bayes_R2()`

method just takes `object`

to be a matrix of y-hat
values (one column per observation, one row per posterior draw) and `y`

to
be a vector with length equal to `ncol(object)`

.

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.
(Preprint,
Notebook)

The rstanarm package (mc-stan.org/rstanarm) for example methods (CRAN, GitHub).

Guidelines and recommendations for developers of R packages interfacing with Stan and a demonstration getting a simple package working can be found in the vignettes included with rstantools and at mc-stan.org/rstantools/articles.