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Comparison of Classical and Bayesian Approaches for Intervention Analysis
Author(s) -
Santos Thiago R.,
Franco Glaura C.,
Gamerman Dani
Publication year - 2010
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2010.00114.x
Subject(s) - outlier , series (stratigraphy) , intervention (counseling) , bayesian probability , state space , mathematics , time series , monte carlo method , computer science , statistics , econometrics , medicine , paleontology , psychiatry , biology
Summary Intervention analysis has been recently the subject of several studies, mainly because real time series present a wide variety of phenomena that are caused by external and/or unexpected events. In this work, transfer functions are used to model different forms of intervention to the mean level of a time series. This is performed in the framework of state‐space models. Two canonical forms of intervention are considered: pulse and step functions. Static and dynamic explanation of the intervention effects, normal and non‐normal time series, detection of intervention, and study of the effect of outliers are also discussed. The performance of the two approaches is compared in terms of point and interval estimation through Monte Carlo simulation. The methodology was applied to real time series and showed satisfactory results for the intervention models used.