saved_states {pomp} | R Documentation |

## Saved states

### Description

Retrieve latent state trajectories from a particle filter calculation.

### Usage

```
## S4 method for signature 'pfilterd_pomp'
saved_states(object, ..., format = c("list", "data.frame"))
## S4 method for signature 'pfilterList'
saved_states(object, ..., format = c("list", "data.frame"))
```

### Arguments

`object` |
result of a filtering computation |

`...` |
ignored |

`format` |
character; format of the returned object (see below). |

### Details

When one calls `pfilter`

with `save.states=TRUE`

, the latent state vector associated with each particle is saved.
This can be extracted by calling `saved_states`

on the ‘pfilterd.pomp’ object.
These are the *unweighted* particles, saved *after* resampling.

### Value

According to the `format`

argument, the saved states are returned either as a list or a data frame.

If `format="data.frame"`

, then the returned data frame holds the state variables and (optionally) the unnormalized log weight of each particle at each observation time.
The `.id`

variable distinguishes particles.

If `format="list"`

and `pfilter`

was called with `save.states="unweighted"`

or `save.states="TRUE"`

, the returned list contains one element per observation time.
Each element consists of a matrix, with one row for each state variable and one column for each particle.
If `pfilter`

was called with `save.states="weighted"`

, the list itself contains two lists:
the first holds the particles as above, the second holds the corresponding unnormalized log weights.
In particular, it has one element per observation time; each element is the vector of per-particle log weights.

### See Also

More on sequential Monte Carlo methods:
`bsmc2()`

,
`cond_logLik()`

,
`eff_sample_size()`

,
`filter_mean()`

,
`filter_traj()`

,
`kalman`

,
`mif2()`

,
`pfilter()`

,
`pmcmc()`

,
`pred_mean()`

,
`pred_var()`

,
`wpfilter()`

Other extraction methods:
`coef()`

,
`cond_logLik()`

,
`covmat()`

,
`eff_sample_size()`

,
`filter_mean()`

,
`filter_traj()`

,
`forecast()`

,
`logLik`

,
`obs()`

,
`pred_mean()`

,
`pred_var()`

,
`spy()`

,
`states()`

,
`summary()`

,
`time()`

,
`timezero()`

,
`traces()`

*pomp*version 5.11.0.0 Index]