AIC.lcc: Akaike and Bayesian Information Criteria for an 'lcc' Object.

Description Usage Arguments Details Author(s) See Also Examples

View source: R/methods.R

Description

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

Usage

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## 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.

Details

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, thiago.paula.oliveira@usp.br

See Also

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

Examples

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## 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)

lcc documentation built on Feb. 26, 2021, 5:07 p.m.

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