From 78b31eedf8ee89f6d16ffece5740e692f23197e2 Mon Sep 17 00:00:00 2001 From: Aki Vehtari Date: Mon, 25 Nov 2024 11:58:21 +0200 Subject: [PATCH] update scrps ref and improve doc --- R/crps.R | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/R/crps.R b/R/crps.R index f805b882..ff1c9e25 100644 --- a/R/crps.R +++ b/R/crps.R @@ -2,11 +2,11 @@ #' #' The `crps()` and `scrps()` functions and their `loo_*()` counterparts can be #' used to compute the continuously ranked probability score (CRPS) and scaled -#' CRPS (SCRPS) (see Bolin and Wallin, 2022). CRPS is a proper scoring rule, and +#' CRPS (SCRPS) (as defined by Bolin and Wallin, 2023). CRPS is a proper scoring rule, and #' strictly proper when the first moment of the predictive distribution is #' finite. Both can be expressed in terms of samples form the predictive -#' distribution. See e.g. Gneiting and Raftery (2007) for a comprehensive -#' discussion on CRPS. +#' distribution. See, for example, a paper by Gneiting and Raftery (2007) +#' for a comprehensive discussion on CRPS. #' #' To compute (S)CRPS, the user needs to provide two sets of draws, `x` and #' `x2`, from the predictive distribution. This is due to the fact that formulas @@ -32,7 +32,7 @@ #' #' @return A list containing two elements: `estimates` and `pointwise`. #' The former reports estimator and standard error and latter the pointwise -#' values. +#' values. Following Bolin & Wallin (2023), a larger value is better. #' #' @examples #' \dontrun{ @@ -47,8 +47,8 @@ #' } #' #' @references -#' Bolin, D., & Wallin, J. (2022). Local scale invariance and robustness of -#' proper scoring rules. arXiv. \doi{10.48550/arXiv.1912.05642} +#' Bolin, D., & Wallin, J. (2023). Local scale invariance and robustness of +#' proper scoring rules. Statistical Science, 38(1):140-159. #' #' Gneiting, T., & Raftery, A. E. (2007). Strictly Proper Scoring Rules, #' Prediction, and Estimation. Journal of the American Statistical Association,