response: Methods for creating depmix response models

Description

Create response objects for depmix models using formulae and family objects.

Usage

GLMresponse(formula, data=NULL, family=gaussian(), pstart=NULL, 
		fixed=NULL, prob=TRUE, ...)
	
	transInit(formula, nstates, data=NULL, family=multinomial(),
		pstart=NULL, fixed=NULL, prob=TRUE, ...)
	
	## S3 method for class 'response':
getdf(object)

Arguments

formula

A model formula.

nstates

The number of states of the model.

family

A family object; currently only multinomial() and gaussian() are allowed options.

data

An optional data.frame to interpret the variables from the formula argument in.

pstart

Starting values for the coefficients and other parameters, ie the standard deviation for the gaussian() family.

fixed

Logical vector indicating which paramters are to be fixed.

prob

Logical indicating whether the starting values for multinomial() family models are probabilities or logistic parameters (see details).

object

Object of class response.

...

Not used currently.

Value

GLMresponse and transInit return objects of class GLMresponse and transInit respectively; both classes extend the response-class. getdf returns the number of free parameters of a response model.

Details

Both methods use the familiar formula interface from linear and general linear models to specify how responses (or transition or prior parameters) depend on covariates. The GLMresponse model is an interface to the glm functions of which the functionality is leant, ie predict, fit and density functions. The transInit response model provides functionality for multinomial responses that are currently fit using nnet (this may change in the future but this should not affect the interface of this function). Note that the transInit model actually lacks a reponse, ie the y-slot is empty, at the time of construction, as the transitions are not observed.