SEsamples {hmmr} | R Documentation |
Bootstrap Samples for Simple 2-State Model
Description
Parametric bootstrap samples for a 2-state hidden Markov model used to compute standard errors.
Usage
data("SEsamples")
Format
A matrix with 1000 rows for each sample, 12 columns for each parameter of the model, including the parameters that are fixed at their boundary values.
Details
The bootstrap sample was generated by the following code:
require(depmixS4) library(hmmr) data(simplehmm) # define the model set.seed(214) mod1 <- depmix(obs~1,data=simplehmm,nstates=2, family=multinomial("identity"), respst=c(.6,0,.4,0,.2,.8), trst=runif(4), inst=c(1,0)) # fit the model fm1 <- fit(mod1,emcontrol=em.control(random.start=FALSE)) # compute bootstrap samples nsamples <- 1000 SEsamples <- matrix(0,ncol=npar(fm1),nrow=nsamples) for(i in 1:nsamples) { sample <- simulate(fm1) fmsam <- fit(sample,emcontrol=em.control(random.start=FALSE)) SEsamples[i,] <- getpars(fmsam) }
Examples
data(SEsamples)
# standard errors
bootses <- apply(SEsamples,2,sd)
bootses[which(bootses==0)] <- NA
bootses
# compare with standard errors from finite differences
library(hmmr)
data(simplehmm)
# define the model
set.seed(214)
mod1 <- depmix(obs~1,data=simplehmm,nstates=2,
family=multinomial("identity"), respst=c(.6,0,.4,0,.2,.8), trst=runif(4), inst=c(1,0))
# fit the model
fm1 <- fit(mod1,emcontrol=em.control(random.start=FALSE))
ses <- cbind(standardError(fm1),bootses)
ses
[Package hmmr version 1.0-0 Index]