SUPERVISED LEARNING TECHNIQUES: REGRESSION and DYNAMIC MODELS. EXAMPLES with EVIEWS

In this book, supervised learning techniques (predictive techniques) related to regression will be developed. More specifically, we will go deeper into the linear models multiple regression with all their problems of identification, estimation and diagnosis. Dynamic models and univariate time series models are also contemplated. Almon, Koyck, Klein, and other dynamic models are developed. An important part of the content is the structural changes and stability in dynamic predictive models, unit roots and co-integration. Finally the book develops univariate time series models across Box and Jenkins Methodology for ARIMA models. Read more