posterior_crossvalidation: Leave-one-out crossvalidation for 'graph_lme' models assuming...

In MetricGraph: Random Fields on Metric Graphs

Leave-one-out crossvalidation for graph_lme models assuming observations at the vertices of metric graphs

Description

Leave-one-out crossvalidation for graph_lme models assuming observations at the vertices of metric graphs

Usage

posterior_crossvalidation(object, factor = 1, tibble = TRUE)

Arguments

object	A fitted model using the graph_lme() function or a named list of fitted objects using the graph_lme() function.
factor	Which factor to multiply the scores. The default is 1.
tibble	Return the scores as a tidyr::tibble()

Value

Vector with the posterior expectations and variances as well as mean absolute error (MAE), root mean squared errors (RMSE), and three negatively oriented proper scoring rules: log-score, CRPS, and scaled CRPS.

MetricGraph documentation built on April 3, 2025, 10:34 p.m.