fitted.gamlss: Extract Fitted Values For A GAMLSS Model

fitted.gamlssR Documentation

Extract Fitted Values For A GAMLSS Model

Description

fitted.gamlss is the GAMLSS specific method for the generic function fitted which extracts fitted values for a specified parameter from a GAMLSS objects. fitted.values is an alias for it. The function fv() is similar to fitted.gamlls() but allows the argument what not to be character

Usage

## S3 method for class 'gamlss'
fitted(object, what = c("mu", "sigma", "nu", "tau"),
                parameter= NULL, ...)
fv(obj, what = c("mu", "sigma", "nu", "tau"), parameter= NULL, ... )

Arguments

object

a GAMLSS fitted model

obj

a GAMLSS fitted model

what

which parameter fitted values are required, default what="mu"

parameter

equivalent to what

...

for extra arguments

Value

Fitted values extracted from the GAMLSS object for the given parameter.

Author(s)

Mikis Stasinopoulos

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

print.gamlss, summary.gamlss, fitted.gamlss, coef.gamlss, residuals.gamlss, update.gamlss, plot.gamlss, deviance.gamlss, formula.gamlss

Examples

data(aids)
h<-gamlss(y~poly(x,3)+qrt, family=PO, data=aids) # 
fitted(h)
rm(h)

mstasinopoulos/GAMLSS-original documentation built on March 27, 2024, 7:11 a.m.