gamlss: gen.likelihood – R documentation

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gen.likelihood

A function to generate the likelihood function from a GAMLSS object

Description

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

Usage

gen.likelihood(object)

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/).

Examples

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

gamlss

Generalised Additive Models for Location Scale and Shape

v5.3-4

GPL-2 | GPL-3

Authors

Mikis Stasinopoulos [aut, cre, cph], Bob Rigby [aut], Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb]

Initial release

2021-03-31