Using the exponential smoothing method requires that residuals are non-correlated. However, in real-life cases, it is quite unlikely that none of the continuous values correlate with each other. Instead, one can use ARIMA in R to build a time series model that takes autocorrelation into consideration. In this recipe, we introduce how to use ARIMA to build a smoothing model.
Please perform the following steps to select the ARIMA model's parameters:
First, simulate an ARIMA process and generate time series data with the
arima.sim
function:> set.seed(123) > ts.sim <- arima.sim(list(order = c(1,1,0), ar = 0.7), n = 100) > plot(ts.sim)
We can then take the difference of the time series:
> ts.sim.diff <- diff(ts.sim)
Plot the differenced time series:
> plot(ts.sim.diff)
Use the...