POMP simulation: Simulations of a partially-observed Markov process

Description

simulate generates simulations of the state and measurement processes.

Usage

## S3 method for class 'pomp':
simulate(object, nsim = 1, seed = NULL, params,
         states = FALSE, obs = FALSE, times, t0,
         as.data.frame = FALSE, include.data = FALSE, \dots)

Arguments

Value

If states=FALSE and obs=FALSE (the default), a list of nsim pomp objects is returned. Each has a simulated data set, together with the parameters used (in slot params) and the state trajectories also (in slot states). If times is specified, then the simulated observations will be at times times. If nsim=1, then a single pomp object is returned (and not a singleton list).
If states=TRUE and obs=FALSE, simulated state trajectories are returned as a rank-3 array with dimensions nvar x (ncol(params)*nsim) x ntimes. Here, nvar is the number of state variables and ntimes the length of the argument times. The measurement process is not simulated in this case.
If states=FALSE and obs=TRUE, simulated observations are returned as a rank-3 array with dimensions nobs x (ncol(params)*nsim) x ntimes. Here, nobs is the number of observables.
If both states=TRUE and obs=TRUE, then a named list is returned. It contains the state trajectories and simulated observations as above.

Details

Simulation of the state process and of the measurement process are each accomplished by a single call to the user-supplied rprocess and rmeasure functions, respectively. This makes it possible for the user to write highly optimized code for these potentially expensive computations.

Examples

Run this code

pompExample(ou2)
x <- simulate(ou2,seed=3495485,nsim=10)
x <- simulate(ou2,seed=3495485,nsim=10,states=TRUE,obs=TRUE)
x <- simulate(ou2,seed=3495485,nsim=10,obs=TRUE,
              as.data.frame=TRUE,include.data=TRUE)