hmmsim2.cont: Simulate a continuous-time hidden Markov series and its...

In ziphsmm: Zero-Inflated Poisson Hidden (Semi-)Markov Models

Description

Simulate a continuous-time hidden Markov series and its underlying states with covariates

Usage

hmmsim2.cont(workparm, M, n, zeroindex, emit_x = NULL, zeroinfl_x = NULL,
  timeindex)

Arguments

workparm	working parameters
M	number of latent states
n	length of the simulated series
zeroindex	a vector specifying whether a certain state is zero-inflated
emit_x	matrix of covariates for the log poisson means. Default to NULL.
zeroinfl_x	matrix of covariates for the nonzero structural zero proportions. Default to NULL.
timeindex	a vector containing the time points

Value

simulated series and corresponding states

References

Walter Zucchini, Iain L. MacDonald, Roland Langrock. Hidden Markov Models for Time Series: An Introduction Using R, Second Edition. Chapman & Hall/CRC

Examples

priorparm <- 0
tpmparm <- c(-1,-2)
zeroindex <- c(1,0)
zeroparm <- c(0,-1,1)
emitparm <- c(2,0.5,-0.5,3,0.3,-0.2)
workparm <- c(priorparm,tpmparm,zeroparm,emitparm)
timeindex <- rep(1,1000)
for(i in 2:1000) timeindex[i] <- timeindex[i-1] + sample(1:4,1)

designx <- matrix(rnorm(2000),nrow=1000,ncol=2)
result <- hmmsim2.cont(workparm,2,1000,zeroindex,emit_x=designx,
                      zeroinfl_x=designx,timeindex=timeindex)
y <- result$series
state <- result$state

ziphsmm documentation built on May 2, 2019, 6:10 a.m.