logLik.nlreg: Compute the Log Likelihood for Nonlinear Heteroscedastic...

In nlreg: Higher Order Inference for Nonlinear Heteroscedastic Models

Compute the Log Likelihood for Nonlinear Heteroscedastic Models

Description

Computes the log likelihood for a nonlinear model with possibly non constant variance.

Usage

## S3 method for class 'nlreg'
logLik(object, ...)

Arguments

object	an object inheriting from class nlreg representing a fitted nonlinear heteroscedastic model.
...	absorbs any additional argument.

Details

This is a method for the function logLik() for objects inheriting from class nlreg.

Value

Returns an object class logLik which is a number with attributes nobs, npar and df giving respectively the number of observations, the number of parameters (regression coefficients plus variance parameters) and the degrees of freedom in the model.

Note

The default print method for logLik objects is used.

See Also

rsm.object, logLik

Examples

library(boot)
data(calcium)
calcium.nl <- nlreg( cal ~ b0*(1-exp(-b1*time)), 
                     start = c(b0 = 4, b1 = 0.1), data = calcium )
logLik( calcium.nl )
##
data(metsulfuron)
metsulfuron.nl <- 
    nlreg( log(area) ~ log( b1+(b2-b1) / (1+(dose/b4)^b3) ), 
           weights = ~ ( 1+dose^exp(g) )^2, data = metsulfuron, 
           start = c(b1 = 138, b2 = 2470, b3 = 2, b4 = 0.07, g = log(0.3)),
           hoa = TRUE )
logLik( metsulfuron.nl )

nlreg documentation built on June 8, 2025, 10:39 a.m.