trajectory: Trajectory of a deterministic model
In kidusasfaw/pomp: Statistical Inference for Partially Observed Markov Processes

Description Usage Arguments Details Value See Also

Compute trajectories of the deterministic skeleton of a Markov process.

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

## S4 method for signature 'traj_match_objfun'
trajectory(object, ...,
  verbose = getOption("verbose", FALSE))

`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. These must be in strictly increasing order.
`t0`	the initial time, i.e., the time corresponding to the initial-state distribution.
`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. Note that this behavior differs from most other functions in pomp. It is not possible to modify the model structure in a call to `trajectory`.
`verbose`	logical; if `TRUE`, more information will be displayed.

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.

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].

skeleton

kidusasfaw/pomp documentation built on May 20, 2019, 2:59 p.m.