# Autoregressive Moving Average Model (ARMA)

Autoregressive Moving Average (ARMA) models are typically applied to autocorrelated time series data. The Autoregressive Moving Average is often called Box–Jenkins models after the iterative Box–Jenkins methodology

# Autoregressive Moving Average (ARMA)

**Autoregressive Moving Average (ARMA)** models are typically applied to autocorrelated time series data. The Autoregressive Moving Average is often called **Box–Jenkins** models after the iterative Box–Jenkins methodology usually used to estimate them.

## Autoregressive Moving Average Model Interpretation

Given a time series of data Xt, the ARMA model is a tool for understanding and, perhaps, predicting future values in this series. The model consists of two parts, an autoregressive part and a moving average part.

The model is usually then referred to as the ARMA(p,q) model where p is the order of the autoregressive part and q is the order of the moving average part.