Description Usage Arguments Value Note Author(s) References See Also Examples

The function computes one-step forecast errors for a filtered dynamic linear model.

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`object` |
an object of class |

`...` |
unused additional arguments. |

`type` |
should standardized or raw forecast errors be produced? |

`sd` |
when |

A vector or matrix (in the multivariate case) of one-step forecast
errors, standardized if `type = "standardized"`

. Time series
attributes of the original observation vector (matrix) are retained by
the one-step forecast errors.

If `sd = TRUE`

then the returned value is a list with the
one-step forecast errors in component `res`

and the corresponding
standard deviations in component `sd`

.

The `object`

argument must include a component `y`

containing the data. This component will not be present if
`object`

was obtained by calling `dlmFilter`

with
`simplify = TRUE`

.

Giovanni Petris [email protected]

Giovanni Petris (2010), An R Package for Dynamic Linear
Models. Journal of Statistical Software, 36(12), 1-16.
http://www.jstatsoft.org/v36/i12/.

Petris, Petrone, and Campagnoli, Dynamic Linear Models with
R, Springer (2009).

West and Harrison, Bayesian forecasting and
dynamic models (2nd ed.), Springer (1997).

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dlm documentation built on June 14, 2018, 1:03 a.m.

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