R: Function to fit finite mixture of gamlss family distributions
gamlssMX
R Documentation
Function to fit finite mixture of gamlss family distributions
Description
The function gamlssMX is design for fitting a K fold non parametric mixture of gamlss family distributions.
Usage
gamlssMX(formula = formula(data), pi.formula = ~1,
family = "NO", weights, K = 2, prob = NULL,
data = sys.parent(), control = MX.control(...),
g.control = gamlss.control(trace = FALSE, ...),
zero.component = FALSE, ...)
gamlssMXfits(n = 5, formula = formula(data), pi.formula = ~1,
family = "NO", weights, K = 2, prob = NULL,
data = sys.parent(), control = MX.control(),
g.control = gamlss.control(trace = FALSE),
zero.component = FALSE, ... )
Arguments
formula
This argument it should be a formula (or a list of formulea of length
K) for modelling the mu parameter of the model. Note that
modelling the rest of the distributional parameters it can be done
by using the usual ... which passes the arguments to
gamlss()
pi.formula
This should be a formula for modelling the prior probabilities as a
function of explanatory variables. Note that no smoothing of other
additive terms are allowed here only the usual linear terms. The
modelling here is done using the multinom() function from
package nnet
family
This should be a gamlss.family distribution (or a list of
distributions). Note that if different distributions are used here
their parameters should be comparable for ease of interpretation.
weights
prior weights if needed
K
the number of finite mixtures with default K=2
prob
prior probabilities if required for starting values
data
the data frame nedded for the fit. Note that this is compulsory if pi.formula is used.
control
This argument sets the control parameters for the EM iterations algorithm.
The default setting are given in the MX.control function
g.control
This argument can be used to pass to gamlss() control parameters, as in
gamlss.control
n
the number of fits required in gamlssMXfits()
zero.component
whether zero component models exist, default is FALSE
...
for extra arguments
Author(s)
Mikis Stasinopoulos and Bob Rigby
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.
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/).
See Also
gamlss, gamlss.family
Examples
library(MASS)
data(geyser)
# fitting 2 finite normal mixtures
m1<-gamlssMX(waiting~1,data=geyser,family=NO, K=2)
## Not run:
#fitting 2 finite gamma mixtures
m2<-gamlssMX(waiting~1,data=geyser,family=GA, K=2)
# fitting a model for pi
# first create a data frame
geyser1<-matrix(0,ncol=2, nrow=298)
geyser1[,1] <-geyser$waiting[-1]
geyser1[,2] <-geyser$duration[-299]
colnames(geyser1)<- c("waiting", "duration")
geyser1 <-data.frame(geyser1)
# get the best of 5 fits
m3<-gamlssMXfits(n=5, waiting~1, pi.formula=~duration, data=geyser1,family=NO, K=2)
m3
## End(Not run)