aic_cat: Akaike information criterion for fitted categorical AD models
In antedep: Antedependence Models for Longitudinal Data
aic_cat R Documentation
Akaike information criterion for fitted categorical AD models
Description
Computes AIC using the fitted log likelihood and a parameter count for
categorical antedependence parameters.
Usage
aic_cat(fit)
Arguments
fit
A fitted model object of class "cat_fit" returned by
fit_cat.
Details
The AIC is computed as:
AIC = -2 \times \ell + 2k
where \ell is the log-likelihood and k is the number of free
parameters.
Value
A numeric scalar AIC value.
Examples
set.seed(1)
y <- simulate_cat(40, 5, order = 1, n_categories = 2)
fit <- fit_cat(y, order = 1)
aic_cat(fit)
antedep documentation built on April 25, 2026, 1:06 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| aic_cat | R Documentation |
Akaike information criterion for fitted categorical AD models
Description
Computes AIC using the fitted log likelihood and a parameter count for categorical antedependence parameters.
Usage
aic_cat(fit)
Arguments
fit |
A fitted model object of class |
Details
The AIC is computed as:
AIC = -2 \times \ell + 2k
where \ell is the log-likelihood and k is the number of free
parameters.
Value
A numeric scalar AIC value.
Examples
set.seed(1)
y <- simulate_cat(40, 5, order = 1, n_categories = 2)
fit <- fit_cat(y, order = 1)
aic_cat(fit)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.