HMMSim: Simulation of an Hidden Markov Model

In RHmm: Hidden Markov Models Simulations and Estimations

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	If not NULL, the state of the previous observation (usefull to complete a serie)

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)
    #Complete the serie.
    simul <- c(simul, HMMSim(1000, hmm_1d_3s, simul$states[1000]))
    

RHmm documentation built on Nov. 30, 2023, 7:22 p.m.