mvgam_diagnostics: Extract diagnostic quantities of 'mvgam' models

In mvgam: Multivariate (Dynamic) Generalized Additive Models

Extract diagnostic quantities of mvgam models

Description

Extract quantities that can be used to diagnose sampling behavior of the algorithms applied by Stan at the back-end of mvgam.

Usage

## S3 method for class 'mvgam'
nuts_params(object, pars = NULL, ...)

## S3 method for class 'mvgam'
log_posterior(object, ...)

## S3 method for class 'mvgam'
rhat(x, pars = NULL, ...)

## S3 method for class 'mvgam'
neff_ratio(object, pars = NULL, ...)

Arguments

object, x	A mvgam object.
pars	An optional character vector of parameter names. For nuts_params these will be NUTS sampler parameter names rather than model parameters. If pars is omitted all parameters are included.
...	Arguments passed to individual methods.

Details

For more details see bayesplot-extractors.

Value

The exact form of the output depends on the method.

Examples

simdat <- sim_mvgam(n_series = 1, trend_model = 'AR1')
mod <- mvgam(y ~ s(season, bs = 'cc', k = 6),
            trend_model = AR(),
            noncentred = TRUE,
            data = simdat$data_train,
            chains = 2)
np <- nuts_params(mod)
head(np)

# extract the number of divergence transitions
sum(subset(np, Parameter == "divergent__")$Value)

head(neff_ratio(mod))

mvgam documentation built on Sept. 11, 2024, 8:55 p.m.