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`

*pomp*version 5.11.0.0 Index]