Description Usage Arguments Details Value Examples

Function `sim_smoother`

performs simulation smoothing i.e. simulates the states
from the conditional distribution *p(α | y, θ)* for linear-Gaussian models.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
sim_smoother(model, nsim, seed, use_antithetic = FALSE, ...)
## S3 method for class 'gaussian'
sim_smoother(
model,
nsim = 1,
seed = sample(.Machine$integer.max, size = 1),
use_antithetic = FALSE,
...
)
## S3 method for class 'nongaussian'
sim_smoother(
model,
nsim = 1,
seed = sample(.Machine$integer.max, size = 1),
use_antithetic = FALSE,
...
)
``` |

`model` |
Model object. |

`nsim` |
Number of independent samples. |

`seed` |
Seed for the random number generator. |

`use_antithetic` |
Use an antithetic variable for location.
Default is |

`...` |
Ignored. |

For non-Gaussian/non-linear models, the simulation is based on the approximating Gaussian model.

An array containing the generated samples.

1 2 3 |

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