sie.predict: Predicting Time Series With H Steps

In Sie2nts: Sieve Methods for Non-Stationary Time Series

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)

Sie2nts documentation built on Jan. 22, 2023, 1:52 a.m.