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pomp (version 0.39-3)

dmeasure-pomp: Evaluate the probability density of observations given underlying states in a partially-observed Markov process

Description

The method dmeasure evaluates the probability density of a set of measurements given the state of the system. This function is part of the low-level interface to pomp objects. This help page does not give instructions on the implementation of models: see pomp for instructions.

Usage

## S3 method for class 'pomp':
dmeasure(object, y, x, times, params, log = FALSE, \dots)

Arguments

object
an object of class pomp.
y
a rank-2 array containing observations. The dimensions of y are nobs x ntimes, where nobs is the number of observables and ntimes is the length of times.
x
a rank-3 array containing the states of the unobserved process. The dimensions of x are nvars x nreps x ntimes, where nvars is the number of state variables, nreps is the nu
times
a numeric vector containing the times at which the observations were made.
params
a rank-2 array of parameters with columns corresponding to the columns of x. Note that the x and params must agree in the number of their columns.
log
if TRUE, log probabilities are returned.
...
at present, these are ignored.

Value

  • Returns a matrix of dimensions nreps x ntimes. If d is the returned matrix, d[j,k] is the likelihood of the observation y[,k] at time times[k] given the state x[,j,k].

Details

This function is essentially a wrapper around the user-supplied dmeasure slot of the pomp object. For specifications on writing such a function, see pomp.

See Also

pomp-class, pomp