HMMSim {RHmm} | R Documentation |
Simulation of an Hidden Markov Model
Description
Simulation of an HMM for different classes of observations distributions
Usage
HMMSim(nSim, HMM, lastState=NULL)
Arguments
nSim |
Number of simulations |
HMM |
An HMMClass object. See HMMSet |
lastState |
Optionnal, value of the previous state of the hidden Markov chain |
Value
a list with
obs |
simulated observations (a vector for univariate distributions, a matrix for multivariate distributions) |
states |
simulated hidden states |
See Also
HMMSet
Examples
# simulate a 3 hidden states model with univariate normal distributions
n_1d_3s <- distributionSet("NORMAL", mean=c(1, -2, 5), var=c(1, 2, 4))
initProb3 <- rep(1,3)/3
transMat3 <- rbind(c(0.5, 0.4, 0.1), c(0.3, 0.4, 0.3), c(0.2, 0.1, 0.7))
hmm_1d_3s <- HMMSet(initProb3, transMat3, n_1d_3s)
simul <- HMMSim(1000, hmm_1d_3s)
#Simulate 1000 more observations
simulMore <- HMMSim(1000, hmm_1d_3s, simul$states[1000])
[Package
RHmm version 1.0.1
Index]