fore.garma.wge: Forecast using a GARMA model

In BivinSadler/tswge: Time Series for Data Science

Forecast using a GARMA model

Description

Find forecasts using a specified GARMA model

Usage

fore.garma.wge(x,u,lambda,phi,theta=0,n.ahead=10,lastn=TRUE,plot=TRUE)

Arguments

x	Realization to be analyzed
u	Parameter u in GARMA model
lambda	Parameter lambda in GARMA model
phi	Coefficients of the AR component of the GARMA model
theta	Coefficients of the MA component of the GARMA model
n.ahead	Number of values to forecast
lastn	If lastn=TRUE then the last n.ahead values are forecast. Otherwise, if lastn=FALSE the next n.ahead values are forecast
plot	If plot=TRUE then plots of the data and forecasts are plotted

Details

Forecasts for an AR model fit to the data are also calculated and optionally plotted

Value

ar.fit.order	Order of the AR model fit to the data
ar.fore	Forecasts based on the AR model
garma.fore	Forecasts based on the GARMA model

Author(s)

Wayne Woodward

References

Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott

Examples

data(llynx)
fore.garma.wge(llynx,u=.796,lambda=.4,phi=.51,theta=0,n.ahead=30,lastn=TRUE,plot=TRUE)

BivinSadler/tswge documentation built on Sept. 15, 2023, 4:07 p.m.