[Depmix-commits] r109 - in trunk: . man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sun Mar 23 16:18:12 CET 2008
Author: ingmarvisser
Date: 2008-03-23 16:18:12 +0100 (Sun, 23 Mar 2008)
New Revision: 109
Added:
trunk/man/
trunk/man/balance.Rd
trunk/man/depmix-class.Rd
trunk/man/depmix-internal.Rd
trunk/man/depmix.Rd
trunk/man/depmix.fit.Rd
trunk/man/depmix.fitted-class.Rd
trunk/man/llratio.Rd
trunk/man/response-class.Rd
trunk/man/response-classes.Rd
trunk/man/response.Rd
trunk/man/speed.Rd
Log:
Fighting with svn
Added: trunk/man/balance.Rd
===================================================================
--- trunk/man/balance.Rd (rev 0)
+++ trunk/man/balance.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,24 @@
+\name{balance}
+
+\docType{data}
+
+\alias{balance}
+
+\title{Balance Scale Data}
+
+\description{Balance scale data of four distance items from 779 subjects;
+participants' ages are included.}
+
+\usage{data(balance)}
+
+\format{Data.frame.}
+
+\source{
+
+ Brenda Jansen (2001),\emph{Development of reasoning on the balance
+ scale task: Psychometric assessment of cognitive strategies}. PhD
+ thesis, University of Amsterdam, Department of Psychology.
+
+}
+
+\keyword{datasets}
Added: trunk/man/depmix-class.Rd
===================================================================
--- trunk/man/depmix-class.Rd (rev 0)
+++ trunk/man/depmix-class.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,69 @@
+\name{depmix-class}
+
+\docType{class}
+
+\alias{depmix-class}
+
+\alias{nresp}
+\alias{nresp,depmix-method}
+
+\alias{ntimes}
+\alias{ntimes,depmix-method}
+
+\title{Class "depmix"}
+
+\description{A \code{\link{depmix}} model.}
+
+\section{Slots}{
+
+ \describe{
+
+ \item{\code{response}:}{List of list of \code{response} objects.}
+
+ \item{\code{transition}}{List of \code{\link{transInit}} objects.}
+
+ \item{\code{prior}:}{\code{\link{transInit}} object.}
+
+ \item{\code{dens}:}{Array of dimension sum(ntimes)*nresp*nstates
+ providing the densities of the observed responses for each state.}
+
+ \item{\code{trDens}:}{Array of dimension \code{sum(ntimes)}*nstates
+ providing the probability of a state transition depending on the
+ predictors.}
+
+ \item{\code{init}:}{Array of dimension \code{length(ntimes)}*nstates with
+ the current predictions for the initial state probabilities.}
+
+ \item{\code{stationary}:}{Logical indicating whether the transitions are
+ time-dependent or not; for internal use.}
+
+ \item{\code{ntimes}:}{A vector containing the lengths of independent time
+ series; if data is provided, sum(ntimes) must be equal to
+ nrow(data).}
+
+ \item{\code{nstates}:}{The number of states of the model.}
+
+ \item{\code{nresp}:}{The number of independent responses.}
+
+ \item{\code{npars}:}{The total number of parameters of the model. This is not
+ the degrees of freedom, ie there are redundancies in the
+ parameters, in particular in the multinomial models for the
+ transitions and prior.}
+
+ }
+}
+
+\section{Accessor Functions}{
+ The following functions should be used for accessing the corresponding
+ slots:
+ \describe{
+ \item{\code{npar}:}{The number of parameters of the model.}
+ \item{\code{nresp}:}{The number of responses.}
+ \item{\code{nstates}:}{The number of states.}
+ \item{\code{ntimes}:}{The vector of independent time series lengths.}
+ }
+}
+
+\author{Ingmar Visser}
+
+\keyword{classes}
Property changes on: trunk/man/depmix-class.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/depmix-internal.Rd
===================================================================
--- trunk/man/depmix-internal.Rd (rev 0)
+++ trunk/man/depmix-internal.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,59 @@
+\name{depmix-internal}
+
+\alias{dens}
+\alias{em}
+\alias{fb}
+\alias{logDens}
+\alias{lystig}
+
+\alias{makeDepmix}
+\alias{makePriorModel}
+\alias{makeResponseModels}
+\alias{makeTransModels}
+
+\alias{mlogit}
+\alias{multinomial}
+\alias{nstates}
+\alias{pa2conr}
+\alias{viterbi}
+\alias{viterbi.fb}
+
+\alias{dens,GLMresponse-method}
+\alias{dens,BINOMresponse-method}
+\alias{dens,NORMresponse-method}
+\alias{dens,MULTINOMresponse-method}
+\alias{dens,transInit-method}
+
+\alias{fit,GLMresponse-method}
+\alias{fit,BINOMresponse-method}
+\alias{fit,NORMresponse-method}w
+\alias{fit,MULTINOMresponse-method}
+\alias{fit,MVNresponse-method}
+\alias{fit,transInit-method}
+
+\alias{logLik,GLMresponse-method}
+
+\alias{predict,GLMresponse-method}
+\alias{predict,BINOMresponse-method}
+\alias{predict,NORMresponse-method}
+\alias{predict,MULTINOMresponse-method}
+\alias{predict,transInit-method}
+
+\alias{getpars,GLMresponse-method}
+\alias{setpars,GLMresponse-method}
+
+\alias{npar,response-method}
+
+\title{Depmix internal functions}
+
+\description{
+ Internal depmix functions, methods and classes.
+}
+
+\details{
+ These are not to be called by the user.
+}
+
+\author{Ingmar Visser}
+
+\keyword{methods}
Property changes on: trunk/man/depmix-internal.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/depmix.Rd
===================================================================
--- trunk/man/depmix.Rd (rev 0)
+++ trunk/man/depmix.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,235 @@
+
+\name{depmix}
+
+\docType{methods}
+
+\alias{depmixS4}
+\alias{depmix}
+\alias{depmix,ANY-method}
+
+\alias{logLik}
+\alias{logLik,depmix-method}
+
+\alias{AIC}
+\alias{AIC,depmix-method}
+
+\alias{BIC}
+\alias{BIC,depmix-method}
+
+\alias{nobs}
+\alias{nobs,depmix-method}
+
+\alias{npar}
+\alias{npar,depmix-method}
+
+\alias{freepars}
+\alias{freepars,depmix-method}
+
+\alias{setpars}
+\alias{setpars,depmix-method}
+
+\alias{getpars}
+\alias{getpars,depmix-method}
+
+\alias{show,depmix-method}
+\alias{summary,depmix-method}
+
+\title{Dependent Mixture Model Specifiction}
+
+\description{
+
+ depmixS4 is a framework for specifying and fitting dependent mixture
+ models, otherwise known as hidden or latent Markov models.
+ Optimization is done with the EM algorithm or optionally with Rdonlp2
+ when constraints on parameters are imposed. Models for different
+ distributions can easily be added.
+
+ \code{depmix} creates an object of class \code{depmix}, a
+ dependent mixture model, otherwise known as hidden Markov
+ model.
+
+}
+
+\usage{
+
+ depmix(response, data=NULL, nstates, transition=~1, family=gaussian(),
+ prior=~1, initdata=NULL, respstart=NULL, trstart=NULL, instart=NULL,
+ ntimes=NULL,...)
+
+ \S4method{summary}{depmix}(object)
+ \S4method{logLik}{depmix}(object)
+ \S4method{AIC}{depmix}(object)
+ \S4method{BIC}{depmix}(object)
+ \S4method{nobs}{depmix}(object)
+
+ \S4method{npar}{depmix}(object)
+ \S4method{freepars}{depmix}(object)
+ \S4method{setpars}{depmix}(object,which="pars",...)
+ \S4method{getpars}{depmix}(object,which="pars",...)
+
+}
+
+\arguments{
+ \item{object}{An object with class \code{depmix}.}
+
+ \item{response}{The response to be modeled; either a formula or a list
+ of formulae in the multivariate case. See details.}
+
+ \item{data}{An optional data.frame to interpret the variables in
+ response and transition.}
+
+ \item{nstates}{The number of states of the model.}
+
+ \item{transition}{A one-sided formula specifying the model for the
+ transitions. See details.}
+
+ \item{family}{A family argument for the response. This must be a list
+ of family's if the response is multivariate.}
+
+ \item{prior}{A one-sided formula specifying the density for the prior
+ or initial state probabilities.}
+
+ \item{initdata}{An optional data.frame to interpret the variables
+ occuring in prior. The number of rows of this data.frame must be
+ equal to the number of cases being modeled. See details.}
+
+ \item{respstart}{Starting values for the parameters of the response
+ models.}
+
+ \item{trstart}{Starting values for the parameters of the transition
+ models.}
+
+ \item{instart}{Starting values for the parameters of the prior or
+ initial state probability model.}
+
+ \item{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. If the data argument has an
+ attribute ntimes, then this is used.}
+
+ \item{which}{The default "pars" returns a vector of all parameters of a
+ \code{depmix} object; the alternative value "fixed" return a
+ logical vector of the same length indicating which parameters are
+ fixed. The setpars functions sets parameters (or the logical fixed
+ vector) to new values; \code{setpars} also recomputes the dens,
+ trans and init slots of \code{depmix} objects. Note that the
+ \code{getpars} and \code{setpars} functions for \code{depmix}
+ objects simply call the functions of the same name for the response
+ and transition models.}
+
+ \item{...}{Not used currently.}
+
+}
+
+\details{
+
+ The function \code{depmix} creates an S4 object of class \code{depmix},
+ which needs to be fitted using \code{\link[depmixS4]{depmix.fit}} to
+ optimize the parameters.
+
+ The response model(s) are created by call(s) to
+ \code{\link[depmixS4]{response}} providing the family and optional
+ predictors. If response is a list of formulae, the response's are
+ assumed to be independent conditional on the latent state.
+
+ The transitions are modeled as a multinomial logistic model for each
+ state. Hence, the transition matrix can be modeled as time-dependent,
+ depending on predictors. The prior density is also modeled as a
+ multinomial logistic. Both are created by calls to
+ \code{\link[depmixS4]{transInit}}.
+
+ Starting values may be provided by the respective arguments. The order
+ in which parameters must be provided can be easily studied by using the
+ \code{setpars} function (see example).
+
+ Linear constraints on parameters can be provided as argument to the
+ \code{\link[depmixS4]{depmix.fit}} function.
+
+}
+
+\value{
+
+\code{depmix} returns an object of class \code{depmix} which has the
+following slots:
+
+ \item{response}{A list of a list of response models; the first
+ index runs over states; the second index runs over the independent
+ responses in case a multivariate response is provided.}
+
+ \item{transition}{A list of \code{transInit} models, ie multinomial
+ logistic models with length the number of states.}
+
+ \item{prior}{A multinomial logistic model for the initial state
+ probabilities.}
+
+ \item{dens,trDens,init}{See depmix-class help for details. For internal
+ use.}
+
+ \item{stationary}{Logical indicating whether the transitions are
+ time-dependent or not; for internal use.}
+
+ \item{ntimes}{A vector containing the lengths of independent time
+ series; if data is provided, sum(ntimes) must be equal to
+ nrow(data).}
+
+ \item{nstates}{The number of states of the model.}
+
+ \item{nresp}{The number of independent responses.}
+
+ \item{npars}{The total number of parameters of the model. This is not
+ the degrees of freedom, ie there are redundancies in the
+ parameters, in particular in the multinomial models for the
+ transitions and prior.}
+
+\code{logLik}, \code{AIC}, and \code{BIC} return the respective values
+associated with the current parameter values. \code{nobs} returns the
+number of observations, ie \code{sum(ntimes)} that is used in computing the
+\code{BIC}. \code{npar} returns the number of paramters of a model;
+\code{freepars} returns the number of non-fixed parameters.
+
+}
+
+\author{Ingmar Visser \email{i.visser at uva.nl}}
+
+\seealso{
+
+ \code{\link[depmixS4]{depmix.fit}}, \code{\link{transInit}},
+ \code{\link{response}}.
+
+}
+
+\references{
+
+ On hidden Markov models: Lawrence R. Rabiner (1989). A tutorial on
+ hidden Markov models and selected applications in speech recognition.
+ \emph{Proceedings of IEEE}, 77-2, p. 267-295.
+
+ On latent class models: A. L. McCutcheon (1987). \emph{Latent class
+ analysis}. Sage Publications.
+
+}
+
+\examples{
+
+# create a 2 state model with one continuous and one binary response
+data(speed)
+mod <- depmix(list(rt~1,corr~1),data=speed,nstates=2,family=list(gaussian(),multinomial()))
+# print the model, formulae and parameter values
+mod
+
+# to see the ordering of parameters to use in setpars
+mod <- setpars(mod, value=1:npar(mod))
+mod
+
+# to see which parameters are fixed (by default only baseline parameters in
+# the multinomial logistic models for the transition models and the initial
+# state probabilities model
+mod <- setpars(mod, getpars(mod,which="fixed"))
+mod
+
+
+}
+
+\keyword{methods}
+
+
Property changes on: trunk/man/depmix.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/depmix.fit.Rd
===================================================================
--- trunk/man/depmix.fit.Rd (rev 0)
+++ trunk/man/depmix.fit.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,165 @@
+\name{fit}
+
+\docType{method}
+
+\alias{fit}
+\alias{depmix.fit}
+\alias{fit,depmix-method}
+
+\alias{posterior}
+\alias{posterior,depmix.fitted-method}
+
+\alias{show,depmix.fitted-method}
+\alias{summary,depmix.fitted-method}
+
+\title{Fit depmix models}
+
+\description{
+
+ \code{fit} optimizes parameters of \code{\link{depmix}} models, optionally
+ subject to general linear (in)equality constraints.}
+
+\usage{
+
+ \S4method{fit}{depmix}(object, fixed=NULL, equal=NULL, conrows=NULL,
+ conrows.upper=0, conrows.lower=0, method=NULL,...)
+
+ \S4method{posterior}{depmix.fitted}(object,...)
+ \S4method{summary}{depmix.fitted}(object)
+
+}
+
+\arguments{
+
+ \item{object}{An object of class \code{depmix}.}
+
+ \item{fixed}{Vector of mode logical indicating which parameters should
+ be fixed.}
+
+ \item{equal}{Vector indicating equality constraints; see details.}
+
+ \item{conrows}{Rows of a general linear constraint matrix; see details.}
+
+ \item{conrows.upper, conrows.lower}{Upper and lower bounds for the
+ linear constraints; see details.}
+
+ \item{method}{The optimization method; mostly determined by
+ constraints.}
+
+ \item{...}{Further arguments passed on to the optimization methods.}
+
+}
+
+\details{
+ The method fits depmix models by the EM algorithm if there are no
+ linear constraints on the parameters and if the transition model has
+ no covariates. Otherwise the general optimizer donlp is used which
+ handles general linear (in-)equality constraints.
+
+ Three types of constraints can be specified on the parameters: fixed,
+ equality, and general constraints. Constraint vectors should be of
+ length npar(object). See help on getpars and setpars about the
+ ordering of parameters.
+
+ The \code{equal} argument is used to specify equality constraints:
+ parameters that get the same integer number in this vector are
+ estimated to be equal. Any integers can be used in the vector except 0
+ and 1, which indicate fixed and free parameters respectively.
+
+ Using the donlp optimizer a Newton-Raphson scheme is employed to
+ estimate parameters subject to linear constraints by imposing:
+
+ bl <= A*x <= bu,
+
+ where x is the parameter vector, bl is a vector of lower bounds, bu
+ is a vector of upper bounds, and A is the constraint matrix.
+
+ The \code{conrows} argument is used to specify rows of A directly, and
+ the conrows.lower and conrows.upper arguments to specify the bounds on
+ the constraints. \code{conrows} is a matrix of npar(object) columns and
+ one row for each constraint (ie a vector in the case of a single
+ constraint).
+
+ \code{llratio} performs a log-likelihood ratio test on two
+ \code{fit}ted models; the first object should have the largest degrees
+ of freedom.
+
+}
+
+\value{
+
+ \code{fit} returns an object of class \code{\link[depmix.fitted-class]{depmix.fitted}} which contains
+ the original depmix object, and further has slots:
+
+ \item{message}{: Convergence information.}
+
+ \item{conMat}{: The constraint matrix A, see details.}
+
+ \item{posterior}{: Returns a data.frame with nstates(object) + 1
+ columns; the first column has the viterbi states, the other columns
+ have the delta probabilities, see Rabiner (1989).}
+
+ The print method shows the \code{message} and the summary method
+ shows the parameter estimates.
+
+}
+
+\references{
+
+ Lawrence R. Rabiner (1989). A tutorial on hidden Markov models and
+ selected applications in speech recognition. \emph{Proceedings of
+ IEEE}, 77-2, p. 267-295.
+
+}
+
+\examples{
+
+data(speed)
+# 2-state model on the RTs of the speed data with random
+# starting values for the transition pars (without those EM does not get off the ground)
+set.seed(1)
+mod <- depmix(rt~1,data=speed,nstates=2,trstart=runif(4))
+# fit the model
+mod1 <- fit(mod)
+mod1 # to see the logLik and optimization information
+# to see the parameters
+summary(mod1)
+
+
+data(balance)
+# four binary items on the balance scale task
+
+# now fit some latent class models
+trstart=c(1,0,0,1) # as this is a latent class model, the transition are not optimized
+instart=c(0.5,0.5)
+set.seed(1)
+respstart=runif(16)
+# note that ntimes argument is used to make this a mixture model
+mod <- depmix(list(d1~1,d2~1,d3~1,d4~1), data=balance, nstates=2,
+ family=list(multinomial(),multinomial(),multinomial(),multinomial()),
+ respstart=respstart,trstart=trstart,instart=instart,
+ ntimes=rep(1,nrow(balance)))
+
+mod1 <- fit(mod)
+
+# add age as covariate on class membership by using the prior argument
+trstart=c(1,0,0,1) # as this is a latent class model, the transition are not optimized
+instart=c(0.5,0.5,0,0) # we need the initial probs and the coefficients of age
+set.seed(2)
+respstart=c(runif(16))
+trstart=c(1,0,0,1)
+mod2 <- depmix(list(d1~1,d2~1,d3~1,d4~1), data=balance, nstates=2,
+ family=list(multinomial(),multinomial(),multinomial(),multinomial()),
+ trstart=trstart, instart=instart, respstart=respstart,
+ ntimes=rep(1,nrow(balance)), prior=~age, initdata=balance)
+
+mod3 <- fit(mod2)
+
+# check the likelihood ratio; adding age significantly improves the goodness-of-fit
+llratio(mod3,mod1)
+
+}
+
+\author{Ingmar Visser}
+
+\keyword{methods}
Property changes on: trunk/man/depmix.fit.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/depmix.fitted-class.Rd
===================================================================
--- trunk/man/depmix.fitted-class.Rd (rev 0)
+++ trunk/man/depmix.fitted-class.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,74 @@
+\name{depmix.fitted-class}
+
+\docType{class}
+
+\alias{depmix.fitted-class}
+
+\title{Class "depmix.fitted"}
+
+\description{A fitted \code{\link{depmix}} model.}
+
+\section{Slots}{
+
+ A \code{depmix.fitted} object is a \code{depmix} object with three
+ additional slots, here is the complete list:
+
+ \describe{
+
+ \item{\code{response}:}{List of list of \code{response} objects.}
+
+ \item{\code{transition}}{List of \code{transInit} objects.}
+
+ \item{\code{prior}:}{\code{transInit} object.}
+
+ \item{\code{dens}:}{Array of dimension sum(ntimes)*nresp*nstates
+ providing the densities of the observed responses for each state.}
+
+ \item{\code{trDens}:}{Array of dimension \code{sum(ntimes)}*nstates
+ providing the probability of a state transition depending on the
+ predictors.}
+
+ \item{\code{init}:}{Array of dimension \code{length(ntimes)}*nstates with
+ the current predictions for the initial state probabilities.}
+
+ \item{\code{stationary}:}{Logical indicating whether the transitions are
+ time-dependent or not; for internal use.}
+
+ \item{\code{ntimes}:}{A vector containing the lengths of independent time
+ series; if data is provided, sum(ntimes) must be equal to
+ nrow(data).}
+
+ \item{\code{nstates}:}{The number of states of the model.}
+
+ \item{\code{nresp}:}{The number of independent responses.}
+
+ \item{\code{npars}:}{The total number of parameters of the model. This is not
+ the degrees of freedom, ie there are redundancies in the
+ parameters, in particular in the multinomial models for the
+ transitions and prior.}
+
+ \item{\code{message}:}{This provides some information on convergence,
+ either from the EM algorithm or from Rdonlp2.}
+
+ \item{\code{conMat}:}{The linear constraint matrix, which has zero rows
+ if there were no constraints.}
+
+ \item{\code{posterior}:}{Posterior (Viterbi) state sequence (not
+ implemented currently).}
+ }
+}
+
+\section{Details}{
+
+ The print function shows some convergence information, and the summary
+ method shows the parameter estimates.
+
+}
+
+\section{Extends}{
+ \code{depmix.fitted} extends the \code{depmix} class.
+}
+
+\author{Ingmar Visser}
+
+\keyword{classes}
Property changes on: trunk/man/depmix.fitted-class.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/llratio.Rd
===================================================================
--- trunk/man/llratio.Rd (rev 0)
+++ trunk/man/llratio.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,49 @@
+
+\name{llratio}
+
+\docType{methods}
+
+\alias{llratio}
+
+\alias{loglikelihoodratio}
+
+\alias{show,llratio-method}
+
+\title{Log likelihood ratio test on two fitted models}
+
+\description{Performs a log likelihood ratio test on two fitted
+\code{depmix} models.}
+
+\usage{
+
+ llratio(basemodel, constrainedmodel, ...)
+
+}
+
+\arguments{
+
+ \item{basemodel}{Fitted model with a \code{logLik} method.}
+
+ \item{constrainedmodel}{Fitted model with a \code{logLik} method.}
+
+ \item{...}{Not currently used.}
+
+}
+
+\value{
+
+ \code{llratio} returns an object of class \code{llratio} which has slots:
+
+ \item{value}{: Minus twice the loglikelihood difference.}
+
+ \item{df}{: The degrees of freedom, ie the difference in number of freely
+ estimated paraemters between the models.}
+
+ The print method shows the value, the degrees of freedom and the
+ corresponding p-value under the chisquared distribution.
+
+}
+
+\author{Ingmar Visser}
+
+\keyword{methods}
\ No newline at end of file
Added: trunk/man/response-class.Rd
===================================================================
--- trunk/man/response-class.Rd (rev 0)
+++ trunk/man/response-class.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,58 @@
+\name{response-class}
+
+\docType{class}
+
+\alias{response-class}
+
+\title{Class "response"}
+
+\description{
+
+A generic \code{\link{response}} model for \code{\link{depmix}} models.
+
+}
+
+\arguments{
+ \item{object}{An object of class "response".}
+}
+
+\section{Slots}{
+
+ \describe{
+ \item{\code{parameters}:}{A (named) list of parameters.}
+
+ \item{\code{fixed}:}{A logical vector indicating which parameters
+ are fixed.}
+
+ \item{\code{y}:}{A matrix with the actual response; possibly
+ multivariate.}
+
+ \item{\code{x}:}{A design matrix; possibly only an intercept term.}
+
+ \item{\code{npar}:}{The number of parameters.}
+ }
+
+}
+
+\details{
+
+ This class offers a framework from which to build specific response
+ models such as glm based responses or multinomial responses. For
+ extensibility, objects with class \code{response} should have at least
+ methods: \code{dens} to return the \code{dens}'ity of responses, and
+ \code{getpars} and \code{setpars} methods to get and set parameters.
+
+}
+
+\section{Accessor Functions}{
+ The following functions should be used for accessing the corresponding
+ slots:
+ \describe{
+ \item{\code{npar}:}{The number of parameters of the model.}
+ \item{\code{getdf}:}{The number of non-fixed parameters.}
+ }
+}
+
+\author{Ingmar Visser}
+
+\keyword{classes}
Property changes on: trunk/man/response-class.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/response-classes.Rd
===================================================================
--- trunk/man/response-classes.Rd (rev 0)
+++ trunk/man/response-classes.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,58 @@
+\name{response-classes}
+
+\docType{class}
+
+\alias{response-classes}
+
+\alias{GLMresponse-class}
+\alias{transInit-class}
+
+\title{Class "GLmresponse" and class "transInit"}
+
+\description{Specific instances of response models for \code{\link{depmix}}
+models.}
+
+\section{Slots}{
+
+ Both \code{GLMresponse} and \code{transInit} contain the
+ \code{response}-class. In addition to the slots of that class, these
+ classes have the following slots:
+
+ \describe{
+
+ \item{\code{formula}:}{A formula that specifies the model.}
+
+ \item{\code{family}:}{A family object specifying the link
+ function. Currently, the only options are \code{gaussian()} from
+ the \code{\link{stats}}-package and \code{multinomial}.}
+ }
+
+}
+
+\details{
+
+ The \code{GLMresponse}-class offers an interface to the
+ \code{\link[stats]{glm}} functions that are subsequently used in fitting
+ the \code{depmix} model of which the response is a part.
+
+ The \code{transInit} is an extension of \code{response} that is used to
+ model the transition matrix and the initial state probabilities by the
+ use of a multinomial logistic model, the difference being that in fact
+ the response is missing as the transitions between states are not
+ observed. This class has its own fit function which is an interface to
+ the multinom function in \code{\link{nnet}}.
+
+}
+
+\section{Accessor Functions}{
+ The following functions should be used for accessing the corresponding
+ slots:
+ \describe{
+ \item{\code{npar}:}{The number of parameters of the model.}
+ \item{\code{getdf}:}{The number of non-fixed parameters.}
+ }
+}
+
+\author{Ingmar Visser}
+
+\keyword{classes}
Property changes on: trunk/man/response-classes.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/response.Rd
===================================================================
--- trunk/man/response.Rd (rev 0)
+++ trunk/man/response.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,85 @@
+\name{response}
+
+\docType{method}
+
+\alias{response}
+\alias{transInit}
+\alias{GLMresponse}
+
+\alias{transInit,formula-method}
+\alias{GLMresponse,formula-method}
+
+\alias{getdf}
+\alias{getdf,response-method}
+
+\alias{show,GLMresponse-method}
+
+\title{Methods for creating depmix response models}
+
+\description{
+
+Create \code{response} objects for \code{\link{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, ...)
+
+ \S4method{getdf}{response}(object)
+}
+
+\arguments{
+ \item{formula}{A model formula.}
+ \item{nstates}{The number of states of the model.}
+ \item{family}{A family object; currently only multinomial() and
+ gaussian() are allowed options.}
+ \item{data}{An optional data.frame to interpret the variables from the
+ formula argument in.}
+ \item{pstart}{Starting values for the coefficients and other
+ parameters, ie the standard deviation for the gaussian() family.}
+ \item{fixed}{Logical vector indicating which paramters are to be fixed.}
+ \item{prob}{Logical indicating whether the starting values for
+ multinomial() family models are probabilities or logistic
+ parameters (see details).}
+ \item{object}{Object of class response.}
+ \item{...}{Not used currently.}
+}
+
+\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.
+
+}
+
+\value{
+
+ \code{GLMresponse} and \code{transInit} return objects of class
+ \code{GLMresponse} and \code{transInit} respectively; both classes
+ extend the \code{\link{response-class}}.
+
+ \code{getdf} returns the number of free parameters of a
+ \code{response} model.
+
+}
+
+\author{Ingmar Visser}
+
+\keyword{methods}
Property changes on: trunk/man/response.Rd
___________________________________________________________________
Name: svn:executable
+ *
Added: trunk/man/speed.Rd
===================================================================
--- trunk/man/speed.Rd (rev 0)
+++ trunk/man/speed.Rd 2008-03-23 15:18:12 UTC (rev 109)
@@ -0,0 +1,36 @@
+\name{speed}
+
+\docType{data}
+
+\alias{speed}
+
+\title{Speed Accuracy Switching Data}
+
+\description{
+
+ This data set is a bivariate series of reaction times and accuracy
+ scores of a single subject switching between slow and accurate
+ responding and fast guessing on a lexical decision task. The slow and
+ accurate responding, and the fast guessing can be modelled using two
+ states, with a switching regime between them. The dataset further
+ contains a third variable called Pacc, representing the relative
+ pay-off for accurate responding, which is on a scale of zero to one.
+ The value of Pacc was varied during the experiment to induce the
+ switching. This data set is a from a single subject from experiment 2
+ in \cite{Van der Maas et al, 2005}.
+
+}
+
+\usage{data(speed)}
+
+\format{Data.frame}
+
+\source{
+
+ Han L. J. Van der Maas, Conor V. Dolan and Peter C. M. Molenaar (2007),
+ Phase Transitions in the Trade-Off between Speed and Accuracy in Choice
+ Reaction Time Tasks. \emph{Manuscript in preparation}.
+
+}
+
+\keyword{datasets}
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