dmeasure-pomp {pomp}R Documentation

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

Description

The method dmeaure evaluates the probability density of a set of measurements given the state of the system.

Usage

dmeasure(object, y, x, times, params, log = FALSE, ...)
## S4 method for signature 'pomp':
dmeasure(object, y, x, times, params, log = FALSE, ...)

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 number of replicates, and ntimes is the length of times. Note that if ntimes != length(times) or ntimes != ncol(y), an error is generated.
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, probabilities p are given as log(p).
... at present, these are ignored.

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.

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].

Author(s)

Aaron A. King (kingaa at umich dot edu)

See Also

pomp-class, pomp


[Package pomp version 0.22-6 Index]