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, ...)The object to use.
Arguments passed to methods. See the methods in the rstanarm package for examples.
For the default method, a vector of y values the same length
as the number of columns in the matrix used as object.
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.