dlm (version 0.7-1)

residuals.dlmFiltered: One-step forecast errors

Description

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

Usage

## S3 method for class 'dlmFiltered':
residuals(object, ..., type = c("standardized", "raw"), sd = TRUE)

Arguments

object

An object of class "dlmFiltered", such as the output from dlmFilter.

...

Unused additional arguments.

type

Should standardized or raw forecast errors be produced?

sd

When TRUE, standard deviations are returned as well.

Value

• 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.

References

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

See Also

dlmFilter

Examples

## diagnostic plots 
nileMod <- dlmModPoly(1, dV = 15099.8, dW = 1468.4)
nileFilt <- dlmFilter(Nile, nileMod)
res <- residuals(nileFilt, sd=FALSE)
qqnorm(res)
tsdiag(nileFilt)