| fore.sigplusnoise.wge {tswge} | R Documentation |
Forecasting signal plus noise models
Description
Forecast models of the form line plus AR noise or cosine plus AR noise with known frequency
Usage
fore.sigplusnoise.wge(x,linear=TRUE,method="mle",freq=0,max.p=5,
n.ahead=10,lastn=FALSE,plot=TRUE,alpha=.05,limits=TRUE)Arguments
x |
The variable containing the realization to be analyzed |
linear |
If TRUE then the program forecasts a line plus noise model. If FALSE the model is cosine plus noise |
method |
Estimation method |
freq |
Frequency of the cosine term. freq is ignored when using line plus noise |
max.p |
Max value of p for the ARp model fit to the noise |
n.ahead |
The number of steps ahead to forecast |
lastn |
If TRUE then the function forecasts the last n.ahead values of the realization. If FALSE the the forecasts are for n.ahead steps beyond the end of the realization |
plot |
If TRUE then the forecasts and realization are plotted |
alpha |
Significance level |
limits |
If TRUE the forecast limits calculated and plotted |
Value
f |
The n.ahead forecasts |
ll |
The lower limits for the forecasts. zeros are returned if limits were not requested |
ul |
The upper limits for the forecasts. zeros are returned if limits were not requested |
res |
Residuals |
wnv |
The estimated white noise variance based on the residuals |
se |
se is the estimated standard error of the k step ahead forecast. zeros are returned if limits were not requested |
xi |
xi is the kth psi weight associated with the fitted AR model and used to calculate the se above. Note that psi0 is1. zeros are returned if limits were not requested |
Author(s)
Wayne Woodward
References
"Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott
Examples
data(llynx)
llynx.for=fore.sigplusnoise.wge(llynx,linear=FALSE,freq=.1,max.p=5,n.ahead=20)