SimHMMGen: Simulation of univariate hidden Markov model

In GenHMM1d: Goodness-of-Fit for Univariate Hidden Markov Models

Description

This function simulates observation from a univariate hidden Markov model

Usage

SimHMMGen(Q, family, theta, n, graph = 0)

Arguments

Q	transition probability matrix; (r x r)
family	distribution name; run the function distributions() for help
theta	parameters; (r x p)
n	number of simulated observations
graph	1 for a graph, 0 otherwise (default); only for continuous distributions

Details

HMM observations simulation

Value

SimData	Simulated data
MC	Simulated Markov chain
Sim	Simulated Data for each regime

Examples

family = "gaussian"
Q = matrix(c(0.8, 0.3, 0.2, 0.7), 2, 2) ; theta = matrix(c(-1.5, 1.7, 1, 1),2,2) ;
sim = SimHMMGen(Q, family, theta, 500, 0)



family = "binomial"
size = 5
Q = matrix(c(0.8, 0.3, 0.2, 0.7), 2, 2) ; thetaB = matrix(c(size, size, 0.2, 0.7),2,2) ;
simB = SimHMMGen(Q, family, thetaB, 500, graph=0)$SimData

GenHMM1d documentation built on Jan. 21, 2021, 9:07 a.m.