# hmmsim2: Simulate a hidden Markov series and its underlying states... In ziphsmm: Zero-Inflated Poisson Hidden (Semi-)Markov Models

## Description

Simulate a hidden Markov series and its underlying states with covariates

## Usage

 ```1 2``` ```hmmsim2(workparm, M, n, zeroindex, prior_x = NULL, tpm_x = NULL, emit_x = NULL, zeroinfl_x = NULL) ```

## 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 `prior_x` matrix of covariates for generalized logit of prior probabilites (excluding the 1st probability). Default to NULL. `tpm_x` matrix of covariates for transition probability matrix (excluding the 1st column). Default to NULL. `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.

## Value

a matrix with 1st column of simulated series and 2nd column of 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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33``` ```## Not run: priorparm <- 0 tpmparm <- c(0,-0.5,0.5,0,-0.2,0.8) 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) designx <- matrix(rnorm(2000),nrow=1000,ncol=2) result <- hmmsim2(workparm,2,1000,zeroindex,tpm_x=designx, emit_x=designx,zeroinfl_x=designx) y <- result\$series prior_init <- c(0.5,0.5) emit_init <- c(10,30) zero_init <- c(0.6,0) omega <- matrix(c(0.9,0.1,0.2,0.8),2,2,byrow=TRUE) fit <- hmmfit(y,NULL,2,prior_init,omega, emit_init,zero_init, emit_x=designx,zeroinfl_x=designx, tpm_x=designx,hessian=FALSE, method="Nelder-Mead", control=list(maxit=2000,trace=1)) decode <- hmmviterbi2(y,NULL,2,fit\$working_parameters,zero_init=c(1,0), emit_x=designx,zeroinfl_x=designx, tpm_x=designx, plot=TRUE, xlab="time", ylab="count", xlim=c(0,360),ylim=c(0,200)) sum(decode!=result\$state) ## End(Not run) ```

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