LS.kalman | R Documentation |
This function run the state-space equations for expansion infinite of moving average in processes LS-ARMA or LS-ARFIMA.
LS.kalman(
series,
start,
order = c(p = 0, q = 0),
ar.order = NULL,
ma.order = NULL,
sd.order = NULL,
d.order = NULL,
include.d = FALSE,
m = NULL
)
series |
(type: numeric) univariate time series. |
start |
(type: numeric) numeric vector, initial values for parameters to run the model. |
order |
(type: numeric) vector corresponding to |
ar.order |
(type: numeric) AR polimonial order. |
ma.order |
(type: numeric) MA polimonial order. |
sd.order |
(type: numeric) polinomial order noise scale factor. |
d.order |
(type: numeric) |
include.d |
(type: numeric) logical argument for |
m |
(type: numeric) truncation order of the MA infinity process. By
default |
The model fit is done using the Whittle likelihood, while the generation of
innovations is through Kalman Filter.
Details about ar.order, ma.order, sd.order
and d.order
can be
viewed in LS.whittle
.
A list with:
residuals |
standard residuals. |
fitted_values |
model fitted values. |
delta |
variance prediction error. |
For more information on theoretical foundations and estimation methods see \insertRefbrockwell2002introductionLSTS \insertRefpalma2007longLSTS \insertRefpalma2013estimationLSTS
fit_kalman <- LS.kalman(malleco, start(malleco))
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