dlmodeler (version 1.4-2)

dlmodeler.build.arima: Build an ARIMA model

Description

Builds an univariate ARIMA DLM of the specified order and coefficients.

Usage

dlmodeler.arima(ar=c(), ma=c(), d=0, sigmaH = NA, sigmaQ = 0, name = "arima")
dlmodeler.build.arima(ar=c(), ma=c(), d=0, sigmaH = NA, sigmaQ = 0, name = "arima")

Arguments

ar

vector of autoregressive coefficients c(ar1, ar2, ar3...).

ma

vector of moving average coefficients c(ma1, ma2, ma3...).

d

order of differenciation.

sigmaH

std dev of the observation disturbance (if unknown, set to NA and use dlmodeler.fit to estimate it). Default = NA.

sigmaQ

std dev of the state disturbances (if unknown, set to NA and use dlmodeler.fit to estimate it). Default = 0.

name

an optional name to be given to the resulting DLM.

Value

An object of class dlmodeler representing the ARIMA model.

Details

The autoregressive terms of the model are $ar[1] + ar[2]L + ... ar[p]L^p$ where $L$ is the lag operator.

The moving average terms of the model are $1 + ma[1]L + ... ma[q]L^q$ where $L$ is the lag operator.

The initial value P0inf is parametered to use exact diffuse initialisation (if supported by the back-end).

References

Durbin, and Koopman, Time Series Analysis by State Space Methods, Oxford University Press (2001), pages 46-48.

See Also

dlmodeler, dlmodeler.build, dlmodeler.build.polynomial, dlmodeler.build.dseasonal, dlmodeler.build.tseasonal, dlmodeler.build.structural, dlmodeler.build.regression

Examples

# Example TODO