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logLik.nlreg

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

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

Higher Order Inference for Nonlinear Heteroscedastic Models

v1.2-2.2
GPL (>= 2) | file LICENCE
Authors
S original by Alessandra R. Brazzale <alessandra.brazzale@unipd.it> and Ruggero Bellio <ruggero.bellio@uniud.it>. R port by Alessandra R. Brazzale <alessandra.brazzale@unipd.it>, following earlier work by Douglas Bates.
Initial release
2019-01-30

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