The function computes one-step forecast errors for a filtered dynamic linear model.
an object of class
unused additional arguments.
should standardized or raw forecast errors be produced?
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.
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
object argument must include a component
containing the data. This component will not be present if
object was obtained by calling
simplify = TRUE.
Giovanni Petris [email protected]
Giovanni Petris (2010), An R Package for Dynamic Linear
Models. Journal of Statistical Software, 36(12), 1-16.
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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