gen.likelihood: A function to generate the likelihood function from a GAMLSS...

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/gen-Likelihood.R

Description

This function generate a function with argument the parameters of the GAMLSS model which can evaluate the log-likelihood function.

Usage

1

Arguments

object

A gamlss fitted model

Details

The purpose of this function is to help the function vcov() to get he right Hessian matrix after a model has fitted. Note that at the momment smoothing terms are consideted as fixed.

Value

A function of the log-likelihood

Author(s)

Mikis Stasinopoulos d.stasinopoulos@londonmet.ac.uk Bob Rigby and Vlasios Voudouris

References

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.

(see also https://www.gamlss.com/).

See Also

vcov

Examples

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5
data(aids)
m1 <- gamlss(y~x+qrt, data=aids, family=NBI)
logL<-gen.likelihood(m1)
logL()
logLik(m1)

Example output

Loading required package: splines
Loading required package: gamlss.data
Loading required package: gamlss.dist
Loading required package: MASS
Loading required package: nlme
Loading required package: parallel
 **********   GAMLSS Version 5.0-2  ********** 
For more on GAMLSS look at http://www.gamlss.org/
Type gamlssNews() to see new features/changes/bug fixes.

GAMLSS-RS iteration 1: Global Deviance = 492.7119 
GAMLSS-RS iteration 2: Global Deviance = 492.6375 
GAMLSS-RS iteration 3: Global Deviance = 492.6373 
[1] 246.3187
'log Lik.' -246.3187 (df=6)

gamlss documentation built on March 31, 2021, 5:10 p.m.