dmeasure {pomp} | R Documentation |
dmeasure workhorse
Description
dmeasure
evaluates the probability density of observations given states.
Usage
## S4 method for signature 'pomp'
dmeasure(
object,
y = obs(object),
x = states(object),
times = time(object),
params = coef(object),
...,
log = FALSE
)
Arguments
object |
an object of class ‘pomp’, or of a class that extends ‘pomp’.
This will typically be the output of |
y |
a matrix containing observations.
The dimensions of |
x |
an array containing states of the unobserved process.
The dimensions of |
times |
a numeric vector (length |
params |
a |
... |
additional arguments are ignored. |
log |
if TRUE, log probabilities are returned. |
Value
dmeasure
returns a matrix of dimensions nreps
x ntimes
.
If d
is the returned matrix, d[j,k]
is the likelihood (or log likelihood if log = TRUE
) of the observation y[,k]
at time times[k]
given the state x[,j,k]
.
See Also
Specification of the measurement density evaluator: dmeasure_spec
More on pomp workhorse functions:
dinit()
,
dprior()
,
dprocess()
,
emeasure()
,
flow()
,
partrans()
,
pomp-package
,
rinit()
,
rmeasure()
,
rprior()
,
rprocess()
,
skeleton()
,
vmeasure()
,
workhorses