Open AccessA first order autoregressive process with a change point: A bayesian approach based on model selection
Author(s) -
Ahmed Hamimes,
Chellai Fatih,
Rachid Benamirouche
Publication year - 2020
Publication title -
afrika statistika
Language(s) - English
Resource type - Journals
ISSN - 2316-090X
DOI - 10.16929/as/2020.2395.165
Subject(s) - autoregressive model , model selection , selection (genetic algorithm) , series (stratigraphy) , bayes factor , bayesian probability , computer science , star model , econometrics , setar , process (computing) , bayesian inference , time series , bayes' theorem , machine learning , artificial intelligence , autoregressive integrated moving average , mathematics , paleontology , biology , operating system
The change points have considerable effects in different areas of applied research. We will use in this work the pseudo-bayes factor in three autoregressive models of order (1); this method permits to analyse the impact of choice between models and allows the use of a simpler technique with model selection in time series. For application, the monthly fluctuations of the DOW-JONES series between January 1999 and September 2009 have been used; we try to detect the financial crisis between 2007 and 2008 to evaluate the model selection method.