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Changes of Variance in First‐Order Autoregressive Time Series Models—With an Application
Author(s) -
Wichern Dean W.,
Miller Robert B.,
Hsu DerAnn
Publication year - 1976
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2347232
Subject(s) - autoregressive model , star model , series (stratigraphy) , variance (accounting) , econometrics , autoregressive integrated moving average , statistics , setar , time series , mathematics , nonlinear autoregressive exogenous model , computer science , economics , geology , paleontology , accounting
Summary A two‐stage method is presented for detecting step changes of variance in first‐order autoregressive time series models. Potential change points are initially located using a “moving‐block” procedure. Given initial change points, an iterative likelihood argument is used to develop estimators of the change points, variances and autoregressive parameters. The efficacy of the method is examined with computer simulation experiments, and a numerical example using stock market data is discussed.