sie.predict {Sie2nts} | R Documentation |
Predicting Time Series With H Steps
Description
predict.nts() predicts the time series data basis on the estimation.
Usage
sie.predict(ts, esti.li, h)
Arguments
ts |
The data set which is a time series data typically |
esti.li |
The output from fix.fit() or sie.auto.fit() function |
h |
h indicates the number of forecasting points |
Value
A vector which contains h forecasting points
Examples
set.seed(137)
time.series = c()
n = 1024
v = 25
w = rnorm(n, 0, 1) / v
x_ini = runif(1,0,1)
for(i in 1:n){
if(i == 1){
time.series[i] = 0.2 + 0.6*cos(2*pi*(i/n))*x_ini + w[i] #
} else{
time.series[i] = 0.2 + 0.6*cos(2*pi*(i/n))*time.series[i-1] + w[i]
}
}
res1.2 = fix.fit(time.series, 5, 1, "Legen")
sie.predict(time.series, res1.2, 5)
[Package Sie2nts version 0.1.0 Index]