sim.mmre.trunc: Function to simulate a two state Markov transition truncated...

In cmjt/mmre: Two state Markov models with individual level random effects

Function to simulate a two state Markov transition truncated log-linear model Number simulated will correspond to length of given times and covariate.

Description

Function to simulate a two state Markov transition truncated log-linear model Number simulated will correspond to length of given times and covariate.

Usage

sim.mmre.trunc(par.sim, cov, times, ID, start.state, random, trunc, fit)

Arguments

par.sim	a named list of parameters. Must contain "log_baseline","jump", and "decay" all vectors of length two corresponding to parameters of the off diagonal transition rates. If data being simulated from a random model then must contain element "sig" the standard deviation of the bivariate normal individual level random effect.
cov	a vector of covariate values (i.e., days since exposure)
times	numeric vector of observed times
ID	a character vector of whale Ids for zero meaned mvn independent random effects
start.state	numeric initial state (can only be 1 or 2)
random	logical, should individual random effects be included.
trunc	numeric truncation at which covariate has no effect
fit	a mmre fit object, either supplied or all other armugents

cmjt/mmre documentation built on Oct. 2, 2023, 11:24 p.m.