Box-Jenkins Methodology: Building Time Series Models

This lecture introduces the Box-Jenkins methodology, a framework for constructing time series models. It covers steps such as identifying suitable values for p, d, and q, estimating ARIMA model parameters, and verifying model fitting. Techniques like time series plots, ACF, and PACF are discussed for model identification. Variance calculations and dependence measures are explored, along with least squares estimation and model diagnostics. The lecture concludes with discussions on residuals, model checking, and the importance of stationarity in time series analysis.