| bayes_R2 {rstantools} | R Documentation |
Generic function and default method for Bayesian R-squared
Description
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.
Usage
bayes_R2(object, ...)
## Default S3 method:
bayes_R2(object, y, ...)
loo_R2(object, ...)
Arguments
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 |
Value
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).
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. (Preprint, Notebook)
See Also
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.