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

Source: R/graph_inference.R
posterior_crossvalidation.Rd

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.