dprocess_spec {pomp} | R Documentation

## The latent state process density

### Description

Specification of dprocess.

### Details

Suppose you have a procedure that allows you to compute the probability density of an arbitrary transition from state x1 at time t1 to state x2 at time t2 under the assumption that the state remains unchanged between t1 and t2. Then you can furnish

        dprocess = f

to `pomp`, where `f` is a C snippet or R function that implements your procedure. Specifically, `f` should compute the log probability density.

Using a C snippet is much preferred, due to its much greater computational efficiency. See `Csnippet` for general rules on writing C snippets. The goal of a dprocess C snippet is to fill the variable `loglik` with the log probability density. In the context of such a C snippet, the parameters, and covariates will be defined, as will the times `t_1` and `t_2`. The state variables at time `t_1` will have their usual name (see `statenames`) with a “`_1`” appended. Likewise, the state variables at time `t_2` will have a “`_2`” appended.

If `f` is given as an R function, it should take as arguments any or all of the state variables, parameter, covariates, and time. The state-variable and time arguments will have suffices “`_1`” and “`_2`” appended. Thus for example, if `var` is a state variable, when `f` is called, `var_1` will value of state variable `var` at time `t_1`, `var_2` will have the value of `var` at time `t_2`. `f` should return the log likelihood of a transition from `x1` at time `t1` to `x2` at time `t2`, assuming that no intervening transitions have occurred.

To see examples, consult the demos and the tutorials on the package website.

### Note

It is not typically necessary (or even feasible) to define `dprocess`. In fact, no current pomp inference algorithm makes use of `dprocess`. This functionality is provided only to support future algorithm development.

### Default behavior

By default, `dprocess` returns missing values (`NA`).

### See Also

Other information on model implementation: `Csnippet`, `accumulators`, `covariate_table`, `distributions`, `dmeasure_spec`, `parameter_trans`, `pomp-package`, `prior_spec`, `rinit_spec`, `rmeasure_spec`, `rprocess_spec`, `skeleton_spec`, `transformations`, `userdata`

[Package pomp version 2.3 Index]