simulate-pomp: Running simulations of a partially-observed Markov process

Description

simulate can be used to generate simulated data sets and/or to simulate the state process.

Usage

## S3 method for class 'pomp':
simulate(object, nsim = 1, seed = NULL, params,
         states = FALSE, obs = FALSE, times = time(object,t0=TRUE),
         ...)

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 t0 slot of the created `pomp' objects will be filled with times[1] and the simulated observations will be at times times[-1].
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

data(ou2)
x <- simulate(ou2,seed=3495485,nsim=10)
x <- simulate(ou2,seed=3495485,nsim=10,states=TRUE,obs=TRUE)