Box-Jenkins(ARIMa) Models The Box-Jenkins methodology refers to a set of procedures for identifying and estimating time series models within the class of autoregressive integrated moving average(ARIMA)models ARIMA models are regression models that use lagged values of the dependent variable and/or random disturbance term as explanatory variables ARIMa models rely heavily on the autocorrelation pattern in the data This method applies to both non-seasonal and seasonal data. In this course we will only deal with non-seasonal data2 Box-Jenkins (ARIMA) Models  The Box-Jenkins methodology refers to a set of procedures for identifying and estimating time series models within the class of autoregressive integrated moving average (ARIMA) models.  ARIMA models are regression models that use lagged values of the dependent variable and/or random disturbance term as explanatory variables.  ARIMA models rely heavily on the autocorrelation pattern in the data  This method applies to both non-seasonal and seasonal data. In this course, we will only deal with non-seasonal data