feature issue #1674

R/loo_predict.R

@@ -64,7 +64,9 @@ loo_predict.brmsfit <- function(object, type = c("mean", "var", "quantile"),
   type <- match.arg(type)
   if (is.null(psis_object)) {
     message("Running PSIS to compute weights")
-    psis_object <- compute_loo(object, criterion = "psis", resp = resp, ...)
+    # run loo instead of psis to allow for moment matching
+    loo_object <- loo(object, resp = resp, save_psis = TRUE, ...)
+    psis_object <- loo_object$psis_object
   }
   preds <- posterior_predict(object, resp = resp, ...)
   E_loo_value(preds, psis_object, type = type, probs = probs)
@@ -79,10 +81,11 @@ loo_epred.brmsfit <- function(object, type = c("mean", "var", "quantile"),
                               probs = 0.5, psis_object = NULL, resp = NULL,
                               ...) {
   type <- match.arg(type)
-  # stopifnot_resp(object, resp)
   if (is.null(psis_object)) {
     message("Running PSIS to compute weights")
-    psis_object <- compute_loo(object, criterion = "psis", resp = resp, ...)
+    # run loo instead of psis to allow for moment matching
+    loo_object <- loo(object, resp = resp, save_psis = TRUE, ...)
+    psis_object <- loo_object$psis_object
   }
   preds <- posterior_epred(object, resp = resp, ...)
   E_loo_value(preds, psis_object, type = type, probs = probs)
@@ -106,7 +109,9 @@ loo_linpred.brmsfit <- function(object, type = c("mean", "var", "quantile"),
   type <- match.arg(type)
   if (is.null(psis_object)) {
     message("Running PSIS to compute weights")
-    psis_object <- compute_loo(object, criterion = "psis", resp = resp, ...)
+    # run loo instead of psis to allow for moment matching
+    loo_object <- loo(object, resp = resp, save_psis = TRUE, ...)
+    psis_object <- loo_object$psis_object
   }
   preds <- posterior_linpred(object, resp = resp, ...)
   E_loo_value(preds, psis_object, type = type, probs = probs)

R/pp_check.R

@@ -16,7 +16,7 @@
 #'  If \code{NULL} all draws are used. If not specified,
 #'  the number of posterior draws is chosen automatically.
 #'  Ignored if \code{draw_ids} is not \code{NULL}.
-#' @param prefix The prefix of the \pkg{bayesplot} function to be applied. 
+#' @param prefix The prefix of the \pkg{bayesplot} function to be applied.
 #'  Either `"ppc"` (posterior predictive check; the default)
 #'  or `"ppd"` (posterior predictive distribution), the latter being the same
 #'  as the former except that the observed data is not shown for `"ppd"`.
@@ -53,7 +53,7 @@
 #'
 #' ## get an overview of all valid types
 #' pp_check(fit, type = "xyz")
-#' 
+#'
 #' ## get a plot without the observed data
 #' pp_check(fit, prefix = "ppd")
 #' }
@@ -62,7 +62,7 @@
 #' @export pp_check
 #' @export
 pp_check.brmsfit <- function(object, type, ndraws = NULL, prefix = c("ppc", "ppd"),
-                             group = NULL, x = NULL, newdata = NULL, resp = NULL, 
+                             group = NULL, x = NULL, newdata = NULL, resp = NULL,
                              draw_ids = NULL, nsamples = NULL, subset = NULL, ...) {
   dots <- list(...)
   if (missing(type)) {
@@ -124,7 +124,7 @@ pp_check.brmsfit <- function(object, type, ndraws = NULL, prefix = c("ppc", "ppd
       "error_scatter_avg", "error_scatter_avg_vs_x",
       "intervals", "intervals_grouped",
       "loo_intervals", "loo_pit", "loo_pit_overlay",
-      "loo_pit_qq", "loo_ribbon", 
+      "loo_pit_qq", "loo_ribbon",
       'pit_ecdf', 'pit_ecdf_grouped',
       "ribbon", "ribbon_grouped",
       "rootogram", "scatter_avg", "scatter_avg_grouped",
@@ -147,7 +147,7 @@ pp_check.brmsfit <- function(object, type, ndraws = NULL, prefix = c("ppc", "ppd
   y <- NULL
   if (prefix == "ppc") {
     # y is ignored in prefix 'ppd' plots
-    y <- get_y(object, resp = resp, newdata = newdata, ...) 
+    y <- get_y(object, resp = resp, newdata = newdata, ...)
   }
   draw_ids <- validate_draw_ids(object, draw_ids, ndraws)
   pred_args <- list(
@@ -167,7 +167,7 @@ pp_check.brmsfit <- function(object, type, ndraws = NULL, prefix = c("ppc", "ppd
     object, newdata = newdata, resp = resp,
     re_formula = NA, check_response = TRUE, ...
   )
-  
+
   # prepare plotting arguments
   ppc_args <- list()
   if (prefix == "ppc") {
@@ -185,17 +185,16 @@ pp_check.brmsfit <- function(object, type, ndraws = NULL, prefix = c("ppc", "ppd
       ppc_args$x <- as.numeric(ppc_args$x)
     }
   }
-  if ("psis_object" %in% setdiff(names(formals(ppc_fun)), names(ppc_args))) {
-    ppc_args$psis_object <- do_call(
-      compute_loo, c(pred_args, criterion = "psis")
-    )
-  }
   if ("lw" %in% setdiff(names(formals(ppc_fun)), names(ppc_args))) {
-    ppc_args$lw <- weights(
-      do_call(compute_loo, c(pred_args, criterion = "psis"))
-    )
+    # run loo instead of psis to allow for moment matching
+    loo_object <- do_call(loo, c(pred_args, save_psis = TRUE))
+    ppc_args$lw <- weights(loo_object$psis_object, log = TRUE)
+  } else if ("psis_object" %in% setdiff(names(formals(ppc_fun)), names(ppc_args))) {
+    # some PPCs may only support 'psis_object' but not 'lw' for whatever reason
+    loo_object <- do_call(loo, c(pred_args, save_psis = TRUE))
+    ppc_args$psis_object <- loo_object$psis_object
   }
-  
+
   # censored responses are misleading when displayed in pp_check
   bterms <- brmsterms(object$formula)
   cens <- get_cens(bterms, data, resp = resp)
@@ -213,20 +212,17 @@ pp_check.brmsfit <- function(object, type, ndraws = NULL, prefix = c("ppc", "ppd
     if (!is.null(ppc_args$x)) {
       ppc_args$x <- ppc_args$x[take]
     }
-    if (!is.null(ppc_args$psis_object)) {
-      # tidier to re-compute with subset
-      psis_args <- c(pred_args, criterion = "psis")
-      psis_args$newdata <- data[take, ]
-      ppc_args$psis_object <- do_call(compute_loo, psis_args)
-    }
     if (!is.null(ppc_args$lw)) {
-      ppc_args$lw <- ppc_args$lw[,take]
+      ppc_args$lw <- ppc_args$lw[, take]
+    } else if (!is.null(ppc_args$psis_object)) {
+      # we only need the log weights so the rest can remain unchanged
+      ppc_args$psis_object$log_weights <- ppc_args$psis_object$log_weights[, take]
     }
   }
-  
+
   # most ... arguments are meant for the prediction function
   for_pred <- names(dots) %in% names(formals(prepare_predictions.brmsfit))
   ppc_args <- c(ppc_args, dots[!for_pred])
-  
+
   do_call(ppc_fun, ppc_args)
 }