calc_ic: Calculate Information Criteria (AIC and BIC)

In dRiftDM: Estimating (Time-Dependent) Drift Diffusion Models

Calculate Information Criteria (AIC and BIC)

Description

Computes/Summarizes the Log-Likelihood, Akaike Information Criterion (AIC), and the Bayesian Information Criterion (BIC)

Usage

calc_ic(drift_dm_obj, ...)

Arguments

drift_dm_obj	an object of type drift_dm
...	further arguments (only relevant: k, for the penality of stats::AIC)

Details

The functions calls logLik.drift_dm, and subsequently stats::AIC and stats::BIC

Value

A custom object of class stats_dm (c("fit_stats", "stats_dm", "data.frame")), containing a data frame with columns:

• Log_Like: the input log-likelihood value

• AIC: the calculated AIC value

• BIC: the calculated BIC value

See Also

new_stats_dm(), logLik.drift_dm

dRiftDM documentation built on April 3, 2025, 7:48 p.m.