simulate.hmmspec {mhsmm}R Documentation

Simulation of hidden Markov models

Description

Simulates data from a hidden Markov model

Usage

## S3 method for class 'hmmspec':
simulate(object, nsim, seed = NULL, r=NULL,...)

Arguments

object A hmmspec object
nsim An integer or vector of integers (for multiple sequences) specifying the length of the sequence(s)
seed seed for the random number generator
r The function used to generate observations from the emission distribution
... further arguments passed to or from other methods.

Details

If nsim is a single integer then a HMM of that length is produced. If nsim is a vector of integers, then length(nsim) sequences are generated with respective lengths.

Value

An object of class hmmdata

x A vector of length sum(N) - the sequence(s) of observed values
s A vector of length sum(N) - the sequence(s) of hidden states
N A vector of the length of each observation sequence (used to segment x and s)

Author(s)

Jared O'Connell

References

Rabiner, L. (1989), A tutorial on hidden Markov models and selected applications in speech recognition, Proceedings of the IEEE, 77, 257-286.

See Also

hmmspec, simulate.hmm, hmm, predict.hmm

Examples


J<-3
initial <- rep(1/J,J)
P <- matrix(c(.8,.5,.1,0.05,.2,.5,.15,.3,.4),nrow=J)
b <- list(mu=c(-3,0,2),sigma=c(2,1,.5))
model <- hmmspec(init=initial, trans=P, emission=b,f=dnorm.hsmm)
train <- simulate(model, nsim=100, seed=1234, r=rnorm.hsmm)
plot(train)


[Package mhsmm version 0.3.1 Index]