如何提取并输出使用forecast函数的预测值，ARIMA model in R

Example code with given Fourier series order K

<R>#for daily time series forecasting and plot the forecasting result, ref : http://robjhyndman.com/hyndsight/longseasonality/n <- 2000m <- 200y <- ts(rnorm(n) + (1:n)%%100/30, f=m)fourier <- function(t,terms,period){  n <- length(t)  X <- matrix(,nrow=n,ncol=2*terms)  for(i in 1:terms)  {    X[,2*i-1] <- sin(2*pi*i*t/period)    X[,2*i] <- cos(2*pi*i*t/period)  }  colnames(X) <- paste(c("S","C"),rep(1:terms,rep(2,terms)),sep="")  return(X)}library(forecast)fit <- Arima(y, order=c(2,0,1), xreg=fourier(1:n,4,m))print(fit$aicc)pred = forecast(final_fit, h=2*m, xreg=fourier(n+1:(2*m),final_k,m))plot(pred)# finish plotting the forecasting result.print(pred$mean)# this is the forecasting values in the forecasting interval.# The code below is for writing the forecasting values in the file. ref:http://robjhyndman.com/hyndsight/batch-forecasting/fcast <- matrix(NA, nrow=2*m, ncol=1)fcast[,1] <- pred$meanwrite(t(fcast), file="result.csv", sep=",", ncol=ncol(fcast))</R>

Note

for the code above, we can see that the ‘pred’ is a list. According to the reference for the forecasting function (https://cran.r-project.org/web/packages/forecast/forecast.pdf), it has values list including ‘model’ to ‘fitted’. My trial tells me that pred[[4]] corresponds to pred$mean, i.e. the forecasting values.

Example code with Inferring Fourier series order K

Traversing all the possible K values. Choose the optimal K with the minimal AICc metric.

<R>min_aicc <- 10000000000final_k <- -1final_fit <- NULL for(k in seq(1, 15, by = 1)){fit <- auto.arima(y, seasonal=FALSE, xreg=fourier(1:n,k,m))print(k)print(fit$aicc)    if(fit$aicc < min_aicc)    {        min_aicc <- fit$aicc        final_k <- k        final_fit <- fit    }}print(final_k)print(final_fit$aicc)</R>