The main purpose of this package is to allow the user of the GAMLSS models to fit mixture distributions.
|License:||GPL (version 2 or later)|
This package has two main function the
gamlssMX() which is loosely based on the
flexmix of R and the function
gamlssNP() which is based on the
package of Jochen Einbeck, Ross Darnell and John Hinde (2006) which in turns
is based on several GLIM4 macros originally written by Murray Aitkin and Brian
Francis. It also contains the function
gqz() which is written by Nick Sofroniou and the function
written by Gordon Smyth.
Maintainer: Mikis Stasinopoulos <firstname.lastname@example.org>
Jochen Einbeck, Ross Darnell and John Hinde (2006) npmlreg: Nonparametric maximum likelihood estimation for random effect models, R package version 0.34
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.
Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2003) Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, (see also http://www.gamlss.org/).
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data(enzyme) mmNO <- gamlssMX(enzyme$act~1, family=NO, K=2) mmNO ## Not run: # also to make sure that it reaches the maximum mmNOs <- gamlssMXfits(n=10,enzyme$act~1, family=NO, K=2) fyNO<-dMX(y=seq(0,3,.01), mu=list(1.253, 0.1876), sigma=list(exp(-0.6665 ), exp(-2.573 )), pi=list(0.4079609, 0.5920391 ), family=list("NO","NO") ) hist(enzyme$act,freq=FALSE,ylim=c(0,3.5),xlim=c(0,3),br=21) lines(seq(0,3,.01),fyNO, col="red") # equivalent model using gamlssNP mmNP <- gamlssNP(act~1, data=enzyme, random=~1,sigma.fo=~MASS,family=NO, K=2) ## End(Not run)
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