R/r2_kl.R

In performance: Assessment of Regression Models Performance

#' @title Kullback-Leibler R2
#' @name r2_kullback
#'
#' @description Calculates the Kullback-Leibler-divergence-based
#'   R2 for generalized linear models.
#'
#' @param model A generalized linear model.
#' @param adjust Logical, if `TRUE` (the default), the adjusted R2 value is
#'   returned.
#'
#' @return A named vector with the R2 value.
#'
#' @examples
#' model <- glm(vs ~ wt + mpg, data = mtcars, family = "binomial")
#' r2_kullback(model)
#' @references
#' Cameron, A. C. and Windmeijer, A. G. (1997) An R-squared measure of goodness
#' of fit for some common nonlinear regression models. Journal of Econometrics,
#' 77: 329-342.
#'
#' @export
r2_kullback <- function(model, adjust = TRUE) {
  if (adjust) {
    adj <- model$df.null / model$df.residual
  } else {
    adj <- 1
  }

  klr2 <- 1 - (model$deviance / model$null.deviance) * adj

  names(klr2) <- "Kullback-Leibler R2"
  klr2
}