Sample from the measurement model distribution, given values of the latent states and the parameters.
# S4 method for pomp
rmeasure(
object,
...,
x = states(object),
times = time(object),
params = coef(object)
)
rmeasure
returns a rank-3 array of dimensions
nobs
x nrep
x ntimes
,
where nobs
is the number of observed variables.
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.
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.
a numeric vector (length ntimes
) containing times.
These must be in non-decreasing order.
a npar
x nrep
matrix of parameters.
Each column is treated as an independent parameter set, in correspondence with the corresponding column of x
.
Specification of the measurement-model simulator: rmeasure_spec
More on pomp workhorse functions:
dinit()
,
dmeasure()
,
dprior()
,
dprocess()
,
emeasure()
,
flow()
,
partrans()
,
pomp-package
,
rinit()
,
rprior()
,
rprocess()
,
skeleton()
,
vmeasure()
,
workhorses