AIC.lcc {lcc}

Akaike and Bayesian Information Criteria for an lcc Object.

Description

Calculate the Akaike's 'An Information Criterion' or the BIC or SBC (Schwarz's Bayesian criterion) for an object of class lcc.

Usage

## S3 method for class 'lcc'
AIC(object, ..., k = 2)

## S3 method for class 'lcc'
BIC(object, ...)

Arguments

object

an object inheriting from class lcc, representing a fitted longitudinal concordance correlation function.

...

optional arguments passed to the AIC function.

k

numeric value, use as penalty coefficient for the number of parameters in the fitted model; the default k = 2 is the classical AIC.

Value

A numeric value with the corresponding AIC or BIC value. See methods for AIC objects to get more details.

Author(s)

Thiago de Paula Oliveira, [e-mail]

See Also

lcc, summary.lcc, coef.lcc, vcov.lcc

Examples

## Not run: 
attach(simulated_hue)
fm6 <- lcc(data = simulated_hue, subject = "Fruit",
           resp = "Hue", method = "Method", time = "Time",
           qf = 2, qr = 1, components = TRUE,
           time_lcc = list(n=50, from=min(Time), to=max(Time)))
AIC(fm6)
BIC(fm6)

## End(Not run)