depmixS4 (version 0.2-1)

depmix: Dependent Mixture Model Specifiction: the long way

Description

makeDepmix creates an object of class depmix. This function is meant for full control, e.g. specifying each response model and the transition and prior models 'by hand'. For the default easier specification of models, please see depmix. This function is meant for specifying one's own response models.

Usage

makeDepmix(response, transition, prior, ntimes = NULL, stationary = TRUE, 
    ...)

Arguments

response

A two-dimensional list of response models. See 'Details'.

transition

A list of transition models, each created by a call to transInit on for possibilities of specifying such models. The lenght of this list should be the nubmer of states of the model.

prior

The initial state probabilities model; created through a call to transInit.

ntimes

A vector specifying the lengths of individual, ie independent, time series. If not specified, the responses are assumed to form a single time series.

stationary

Logical indicating whether the transition models include time-varying covariates; used internally to determine the dimensions of certain arrays, notably trDens.

...

Not used currently.

Value

• See the depmix help page for the return value, a depmix object.

Details

The function makeDepmix creates an S4 object of class depmix, which needs to be fitted using fit to optimize the parameters. This function is provided to have full control, eg by specifying one's own response models with distributions that are not provided. The response model(s) should be created by call(s) to response or one's own created response models that should extend the response class and have the following methods: dens, predict and optionally fit. The fit function should have an argument w, providing the weights. If the fit function is not provided, optimization should be done by using Rdonlp (use method="donlp" in calling fit on the depmix model, this is currently not done automatically). The first index of response models runs over the states of the model, and the seconde index over the responses to be modeled.

See Also

fit, transInit, response, depmix-methods for accessor functions to depmix objects.

Examples

# below example recreates the model from the depmix help page albeit in a
# roundabout way

data(speed)   

rModels <- list(
	list(
		GLMresponse(formula=rt~1,data=speed,family=gaussian(),pstart=c(5.52,.202)),
		GLMresponse(formula=corr~1,data=speed,family=multinomial(),pstart=c(0.5,0.5))
	),
	list(
		GLMresponse(formula=rt~1,data=speed,family=gaussian(),pstart=c(6.39,.24)),
		GLMresponse(formula=corr~1,data=speed,family=multinomial(),pstart=c(.1,.9))
	)
)

trstart=c(0.9,0.1,0.1,0.9)

transition <- list()
transition[[1]] <- transInit(~1,nstates=2,data=data.frame(1),pstart=c(trstart[1:2]))
transition[[2]] <- transInit(~1,nstates=2,data=data.frame(1),pstart=c(trstart[3:4]))

instart=c(0,1)
inMod <- transInit(~1,ns=2,ps=instart,data=data.frame(rep(1,3)))

mod <- makeDepmix(response=rModels,transition=transition,prior=inMod,ntimes=attr(speed,"ntimes"))

logLik(mod)

fm <- fit(mod)

fm 

summary(fm)