mcmc_diagnostics: Diagnostic Values of a 'dynamite' Model

In dynamite: Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data

Diagnostic Values of a dynamite Model

Description

Prints HMC diagnostics and lists parameters with smallest effective sample sizes and largest Rhat values. See hmc_diagnostics() and posterior::default_convergence_measures() for details.

Usage

mcmc_diagnostics(x, ...)

## S3 method for class 'dynamitefit'
mcmc_diagnostics(x, n = 3L, ...)

Arguments

x	[dynamitefit] The model fit object.
...	Ignored.
n	[integer(1)] How many rows to print in parameter-specific convergence measures. The default is 3. Should be a positive (unrestricted) integer.

Value

Returns x (invisibly).

See Also

Model diagnostics hmc_diagnostics(), lfo(), loo.dynamitefit()

Examples

data.table::setDTthreads(1) # For CRAN
mcmc_diagnostics(gaussian_example_fit)

dynamite documentation built on April 12, 2025, 1:18 a.m.