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model.frame.gamlss.Rd
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\name{model.frame.gamlss}
\alias{model.frame.gamlss}
\alias{terms.gamlss}
\alias{model.matrix.gamlss}
\title{Extract a model.frame, a model matrix or terms from a GAMLSS object for a given distributional parameter}
\description{
\code{model.frame.gamlss}, \code{model.matrix.gamlss} and \code{terms.gamlss} are the gamlss versions of the generic functions
\code{model.frame}, \code{model.matrix} and \code{terms} respectively.
}
\usage{
\method{model.frame}{gamlss}(formula, what = c("mu", "sigma", "nu", "tau"),
parameter= NULL, ...)
\method{terms}{gamlss}(x, what = c("mu", "sigma", "nu", "tau"),
parameter= NULL, ...)
\method{model.matrix}{gamlss}(object, what = c("mu", "sigma", "nu", "tau"),
parameter= NULL, ...)
}
\arguments{
\item{formula}{a gamlss object}
\item{x}{a gamlss object}
\item{object}{a gamlss object}
\item{what}{for which parameter to extract the model.frame, terms or model.frame }
\item{parameter}{equivalent to \code{what}}
\item{\dots}{for extra arguments}
}
\value{
a model.frame, a model.matrix or terms
}
\references{
Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion),
\emph{Appl. Statist.}, \bold{54}, part 3, pp 507-554.
Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019)
\emph{Distributions for modeling location, scale, and shape: Using GAMLSS in R}, Chapman and Hall/CRC. An older version can be found in \url{https://www.gamlss.com/}.
Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R.
\emph{Journal of Statistical Software}, Vol. \bold{23}, Issue 7, Dec 2007, \url{https://www.jstatsoft.org/v23/i07/}.
Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017)
\emph{Flexible Regression and Smoothing: Using GAMLSS in R}, Chapman and Hall/CRC.
(see also \url{https://www.gamlss.com/}).
}
\author{Mikis Stasinopoulos }
\seealso{ \code{\link{gamlss}} }
\examples{
data(aids)
mod<-gamlss(y~poly(x,3)+qrt, family=PO, data=aids) #
model.frame(mod)
model.matrix(mod)
terms(mod, "mu")
rm(mod)
}
\keyword{regression}%