LOO refactoring and adding pred_measure feature

.gitignore

@@ -16,6 +16,8 @@ loo.Rproj
 # produced vignettes
 vignettes/loo2-lfo_cache/*
 vignettes/loo2-non-factorizable_cache/*
+vignettes/articles-online-only/data-for-vignettes/
+vignettes/articles-online-only/*.html
 vignettes/*.html
 vignettes/*.pdf
 inst/doc

DESCRIPTION

@@ -36,6 +36,7 @@ Depends:
     R (>= 3.1.2)
 Imports:
     checkmate,
+    cli,
     matrixStats (>= 0.52),
     parallel,
     posterior (>= 1.7.0),

NAMESPACE

@@ -21,15 +21,11 @@ S3method(as.psis_loo,psis_loo)
 S3method(as.psis_loo,psis_loo_ss)
 S3method(as.psis_loo_ss,psis_loo)
 S3method(as.psis_loo_ss,psis_loo_ss)
-S3method(crps,matrix)
-S3method(crps,numeric)
 S3method(dim,importance_sampling)
 S3method(dim,kfold)
 S3method(dim,loo)
 S3method(dim,psis_loo)
 S3method(dim,waic)
-S3method(elpd,array)
-S3method(elpd,matrix)
 S3method(importance_sampling,array)
 S3method(importance_sampling,default)
 S3method(importance_sampling,matrix)
@@ -41,11 +37,9 @@ S3method(loo_approximate_posterior,array)
 S3method(loo_approximate_posterior,matrix)
 S3method(loo_compare,default)
 S3method(loo_compare,psis_loo_ss_list)
-S3method(loo_crps,matrix)
 S3method(loo_model_weights,default)
 S3method(loo_moment_match,default)
 S3method(loo_predictive_metric,matrix)
-S3method(loo_scrps,matrix)
 S3method(loo_subsample,"function")
 S3method(nobs,psis_loo_ss)
 S3method(plot,loo)
@@ -57,8 +51,11 @@ S3method(print,compare.loo_ss)
 S3method(print,importance_sampling)
 S3method(print,importance_sampling_loo)
 S3method(print,kfold)
+S3method(print,kfold_pred_measure)
 S3method(print,loo)
+S3method(print,loo_pred_measure)
 S3method(print,pareto_k_table)
+S3method(print,pred_measure)
 S3method(print,pseudobma_bb_weights)
 S3method(print,pseudobma_weights)
 S3method(print,psis)
@@ -83,8 +80,6 @@ S3method(relative_eff,array)
 S3method(relative_eff,default)
 S3method(relative_eff,importance_sampling)
 S3method(relative_eff,matrix)
-S3method(scrps,matrix)
-S3method(scrps,numeric)
 S3method(sis,array)
 S3method(sis,default)
 S3method(sis,matrix)
@@ -100,14 +95,19 @@ export(.compute_point_estimate)
 export(.ndraws)
 export(.thin_draws)
 export(E_loo)
+export(acc)
+export(bacc)
+export(brier)
 export(compare)
-export(crps)
 export(elpd)
+export(elpd.array)
+export(elpd.matrix)
 export(example_loglik_array)
 export(example_loglik_matrix)
 export(extract_log_lik)
 export(find_model_names)
 export(gpdfit)
+export(insample_pred_measure)
 export(is.kfold)
 export(is.loo)
 export(is.psis)
@@ -116,6 +116,7 @@ export(is.sis)
 export(is.tis)
 export(is.waic)
 export(kfold)
+export(kfold_pred_measure)
 export(kfold_split_grouped)
 export(kfold_split_random)
 export(kfold_split_stratified)
@@ -128,33 +129,42 @@ export(loo_approximate_posterior.array)
 export(loo_approximate_posterior.function)
 export(loo_approximate_posterior.matrix)
 export(loo_compare)
-export(loo_crps)
 export(loo_i)
 export(loo_model_weights)
 export(loo_model_weights.default)
 export(loo_moment_match)
 export(loo_moment_match.default)
+export(loo_pred_measure)
 export(loo_predictive_metric)
-export(loo_scrps)
 export(loo_subsample)
 export(loo_subsample.function)
+export(mae)
 export(mcse_loo)
+export(mlpd)
+export(mse)
 export(nlist)
 export(obs_idx)
 export(pareto_k_ids)
 export(pareto_k_influence_values)
 export(pareto_k_table)
 export(pareto_k_values)
 export(pointwise)
+export(pred_measure)
 export(print_dims)
 export(pseudobma_weights)
 export(psis)
 export(psis_n_eff_values)
 export(psislw)
+export(ptw_log_pred_density)
+export(r2)
 export(relative_eff)
-export(scrps)
+export(rmse)
+export(rps)
 export(sis)
+export(srps)
 export(stacking_weights)
+export(supported_measures_list)
+export(test_pred_measure)
 export(tis)
 export(waic)
 export(waic.array)

R/elpd.R

@@ -4,7 +4,6 @@
 #' pointwise predictive density for a new dataset or the log pointwise
 #' predictive density of the observed data (an overestimate of the elpd).
 #'
-#' @export
 #' @param x A log-likelihood array or matrix. The **Methods (by class)**
 #'   section, below, has detailed descriptions of how to specify the inputs for
 #'   each method.
@@ -19,8 +18,8 @@
 #'
 #' @examples
 #' # Calculate the lpd of the observed data
-#' LLarr <- example_loglik_array()
-#' elpd(LLarr)
+#' # LLarr <- example_loglik_array()
+#' # elpd(LLarr)
 #'
 elpd <- function(x, ...) {
   UseMethod("elpd")