ARIMA Function in R: Usage Guide

ARIMA function in R is used for fitting autoregressive integrated moving average (ARIMA) models. ARIMA models are commonly used for time series forecasting and can be utilized to predict future values at specific time points.

The usage of the ARIMA function is as follows:

arima(x, order = c(p, d, q))

In this case, x is the time series data to be fitted in the ARIMA model, and the order parameter is a vector of three integers representing the three parameters in the ARIMA model: p (autoregressive order), d (differencing order), and q (moving average order).

For example, if you want to fit an ARIMA(1,1,1) model, you can use the following code:

fit <- arima(x, order = c(1, 1, 1))

After the fitting is complete, you can use the forecast function to predict future time points.

forecast(fit, h = 10)

This will provide forecasting results for the next 10 time points.