17.7 Forecasting with Time Series Models

time series forecasting was made to predict beyond a point of time
huge field, focusing on ARMA here
AR: autoregression, MA: moveing average
AR(1): \(Y_t = \beta_0 + \beta_1 Y_{t-1} + \epsilon\)
MA(1): \(Y_t = \beta_0 + (\epsilon_t + \theta\epsilon_{t-1})\)
ARMA(2,1): \(Y_t = \beta_0 + \beta_1 Y_{t-1} + \beta_1 Y_{t-2} + (\epsilon_t + \theta\epsilon_{t-1})\)

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