dinit: dinit workhorse

In kingaa/pomp: Statistical Inference for Partially Observed Markov Processes

dinit workhorse

Description

Evaluates the initial-state density.

Usage

## S4 method for signature 'pomp'
dinit(
  object,
  params = coef(object),
  t0 = timezero(object),
  x,
  log = 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.
t0	the initial time, i.e., the time corresponding to the initial-state distribution.
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.
log	if TRUE, log probabilities are returned.
...	additional arguments are ignored.

Value

dinit returns a 1-D numerical array containing the likelihoods (or log likelihoods if log=TRUE). By default, t0 is the initial time defined when the ‘pomp’ object ws constructed.

See Also

Specification of the initial-state distribution: dinit_spec

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

kingaa/pomp documentation built on April 24, 2024, 11:25 a.m.