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#' Compute R-squared between numeric observations and predictions
#'
#' @description
#' Internal function to compute the R-squared of observations versus predictions via \code{stats::cor()}. Used within [f_numeric_glm()], [f_numeric_gam()], [f_numeric_rf()], [f_count_glm()], and [f_count_gam()].
#'
#' @param o (required, numeric vector) Observations. Default: NULL
#' @param p (required, numeric vector) Predictions. Default: NULL
#' @inheritParams collinear
#'
#' @return numeric: Pearson R-squared
#' @export
#' @autoglobal
#' @family modelling_tools
#' @examples
#' score_r2(
#' o = c(1, 1, 1, 0.5, 0.5, 0, 0),
#' p = c(1, 0.8, 0.7, 0.6, 0.5, 0.1, 0)
#' )
score_r2 <- function(
o = NULL,
p = NULL,
...
) {
function_name <- validate_arg_function_name(
default_name = "collinear::score_r2()",
... = ...
)
out <- tryCatch(
{
stats::cor(
x = p,
y = o,
use = "complete.obs",
method = "pearson"
)^2
},
error = function(e) {
stop(
"\n",
function_name,
": ",
conditionMessage(e),
call. = FALSE
)
}
)
out
}
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