skeleton {pomp}R Documentation

skeleton workhorse

Description

Evaluates the deterministic skeleton at a point or points in state space, given parameters. In the case of a discrete-time system, the skeleton is a map. In the case of a continuous-time system, the skeleton is a vectorfield. NB: skeleton just evaluates the deterministic skeleton; it does not iterate or integrate (see flow and trajectory for this).

Usage

## S4 method for signature 'pomp'
skeleton(
  object,
  ...,
  x = states(object),
  times = time(object),
  params = coef(object)
)

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.

...

additional arguments are ignored.

x

an array containing states of the unobserved process. The dimensions of x are nvars x nrep x ntimes, where nvars is the number of state variables, nrep is the number of replicates, and ntimes is the length of times. One can also pass x as a named numeric vector, which is equivalent to the nrep=1, ntimes=1 case.

times

a numeric vector (length ntimes) containing times. These must be in non-decreasing order.

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.

Value

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

See Also

Specification of the deterministic skeleton: skeleton_spec

More on pomp workhorse functions: dinit(), dmeasure(), dprior(), dprocess(), emeasure(), flow(), partrans(), pomp-package, rinit(), rmeasure(), rprior(), rprocess(), vmeasure(), workhorses

More on methods for deterministic process models: flow(), skeleton_spec, traj_match, trajectory()


[Package pomp version 6.1.0.0 Index]