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Diagnostics for epidist_fit models

Source: R/diagnostics.R
epidist_diagnostics.Rd

This function computes diagnostics to assess the quality of a fitted model. When the fitting algorithm used is "sampling" (HMC) then the output of epidist_diagnostics is a data.frame containing:

  • time: the total time taken to fit all chains

  • samples: the total number of samples across all chains

  • max_rhat: the highest value of the Gelman-Rubin statistic

  • divergent_transitions: the total number of divergent transitions

  • per_divergent_transitions: the proportion of samples which had divergent transitions

  • max_treedepth: the highest value of the treedepth HMC parameter

  • no_at_max_treedepth: the number of samples which attained the max_treedepth

  • per_at_max_treedepth: the proportion of samples which attained the max_treedepth

Usage

epidist_diagnostics(fit)

Arguments

fit

A fitted model of class epidist_fit

Details

When the fitting algorithm is not "sampling" (see brms::brm() for other possible algorithms) then diagnostics are yet to be implemented.