fore.arima.wge {tswge}

Function for forecasting from known model which may have (1-B)^d and/or seasonal factors

Description

This function calculates forecasts from a known model that may have stationary ARMA components as well as (1-B)^dand/or seasonal factors

Usage

fore.arima.wge(x,phi=0,theta=0,d=0,s=0,n.ahead=5,lastn=FALSE,plot=TRUE,alpha=.05,limits)

Arguments

x

Realization to be forecast from

phi

Vector containing stationary AR parameters

theta

Vector containing MA parameters

d

Order of difference

s

Seasonal order

n.ahead

Number of steps ahead to forecast

lastn

Logical, lastn=TRUE plots forecasts for the last n.ahead values in the realization

plot

Logical, plot=TRUE plots forecasts

alpha

Significance level for prediction limits

limits

Logical, limits=TRUE plots prediction limits

Value

f

Vector of forecasts

ll

Lower limits

ul

Upper limits

resid

Residuals

wnv

White noise variance estimate

xbar

Sample mean of data in x

se

Se for each forecast

psi

Psi weights

ptot

Total order of all AR components, phi, d, and s

phtot

Coefficients after multiplying all stationary and nonstationary coponents on the AR side of the equation

Author(s)

Wayne Woodward

References

"Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott

Examples

data(airline)
          x=log(airline)
          phi12=c(-.36,-.05,-.14,-.11,.04,.09,-.02,.02,.17,.03,-.1,-.38)
          s=12
          d=1
          fore.arima.wge(x,phi=phi12,d=1,s=12,n.ahead=12,limits=FALSE)