pomp (version 3.6)

trajectory: Trajectory of a deterministic model

Description

Compute trajectories of the deterministic skeleton of a Markov process.

Usage

# S4 method for pomp
trajectory(
  object,
  params,
  times,
  t0,
  format = c("array", "data.frame"),
  ...,
  verbose = getOption("verbose", FALSE)
)
# S4 method for traj_match_objfun
trajectory(object, ..., verbose = getOption("verbose", FALSE))

Arguments

object

an object of class ‘pomp’, or of a class that extends ‘pomp’. This will typically be the output of pomp, simulate, or one of the pomp inference algorithms.

params

a npar x nrep matrix of parameters. Each column is treated as an independent parameter set, in correspondence with the corresponding column of x.

times

a numeric vector (length ntimes) containing times at which the itineraries are desired. These must be in non-decreasing order with times[1]>t0. By default, this is the full set of observation times (see time).

t0

the time at which the initial conditions are assumed to hold. By default, this is the zero-time (see timezero).

format

the format in which to return the results.

format = "array" causes the trajectories to be returned in a rank-3 array with dimensions nvar x ncol(params) x ntimes. Here, nvar is the number of state variables and ntimes the length of the argument times.

format = "data.frame" causes the results to be returned as a single data frame containing the time and states. An ordered factor variable, ‘.id’, distinguishes the trajectories from one another.

...

Additional arguments are passed to the ODE integrator (if the skeleton is a vectorfield) and are ignored if it is a map. See ode for a description of the additional arguments accepted by the ODE integrator. By default, this is the parameter vector stored in object (see coef).

verbose

logical; if TRUE, diagnostic messages will be printed to the console.

Value

trajectory returns an array of dimensions nvar x nrep x ntimes. If x is the returned matrix, x[i,j,k] is the i-th component of the state vector at time times[k] given parameters params[,j].

Details

In the case of a discrete-time system, the deterministic skeleton is a map and a trajectory is obtained by iterating the map. In the case of a continuous-time system, the deterministic skeleton is a vector-field; trajectory uses the numerical solvers in deSolve to integrate the vectorfield.

Note that the handling of … in trajectory differs from that of most other functions in pomp. In particular, it is not possible to modify the model structure in a call to trajectory.

See Also

More on pomp elementary algorithms: elementary algorithms, kalman, pfilter(), pomp-package, probe(), simulate(), spect(), wpfilter()

More on methods for deterministic process models: flow(), skeleton specification, skeleton(), trajectory matching