workhorses {pomp} | R Documentation |

## Workhorse functions for the pomp algorithms.

### Description

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.

### Details

They include

`rinit`

which samples from the initial-state distribution,

`dinit`

which evaluates the initial-state density,

`dmeasure`

which evaluates the measurement model density,

`rmeasure`

which samples from the measurement model distribution,

`emeasure`

which computes the expectation of the observed variables conditional on the latent state,

`vmeasure`

which computes the covariance matrix of the observed variables conditional on the latent state,

`dprocess`

which evaluates the process model density,

`rprocess`

which samples from the process model distribution,

`dprior`

which evaluates the prior probability density,

`rprior`

which samples from the prior distribution,

`skeleton`

which evaluates the model's deterministic skeleton,

`flow`

which iterates or integrates the deterministic skeleton to yield trajectories,

`partrans`

which performs parameter transformations associated with the model.

### Author(s)

Aaron A. King

### See Also

basic model components, elementary algorithms, estimation algorithms

More on pomp workhorse functions:
`dinit()`

,
`dmeasure()`

,
`dprior()`

,
`dprocess()`

,
`emeasure()`

,
`flow()`

,
`partrans()`

,
`pomp-package`

,
`rinit()`

,
`rmeasure()`

,
`rprior()`

,
`rprocess()`

,
`skeleton()`

,
`vmeasure()`

*pomp*version 5.10.0.1 Index]