These functions mediate the interface between the user's model and the package algorithms. They are low-level functions that do the work needed by the package's inference methods.
They include
dmeasurewhich evaluates the measurement model density,
rmeasurewhich samples from the measurement model distribution,
emeasurewhich computes the expectation of the observed variables conditional on the latent state,
vmeasurewhich computes the covariance matrix of the observed variables conditional on the latent state,
dprocesswhich evaluates the process model density,
rprocesswhich samples from the process model distribution,
dpriorwhich evaluates the prior probability density,
rpriorwhich samples from the prior distribution,
skeletonwhich evaluates the model's deterministic skeleton,
flowwhich iterates or integrates the deterministic skeleton to yield trajectories,
partranswhich performs parameter transformations associated with the model.
basic model components, elementary algorithms, estimation algorithms
More on pomp workhorse functions:
dmeasure(),
dprior(),
dprocess(),
emeasure(),
flow(),
partrans(),
pomp-package,
rinit(),
rmeasure(),
rprior(),
rprocess(),
skeleton(),
vmeasure()