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In time series analysis, the stationarity takes an important place. Indeed, stationary processes are more tractable in prcatice and mathematical analysis. In the speciale case of autoregressive models, the stationarity is connected with the unit root problem. Some main published results, such as the famous Dickey-Fuller test, are presented in the first part of the document. Our aim is to study the behavior of this test in presence of contamination. The second part which is independent on the first,treats some aspects of ARCH models (autoregressive conditionally heteroscedastic) that are non…mehr

Produktbeschreibung
In time series analysis, the stationarity takes an important place. Indeed, stationary processes are more tractable in prcatice and mathematical analysis. In the speciale case of autoregressive models, the stationarity is connected with the unit root problem. Some main published results, such as the famous Dickey-Fuller test, are presented in the first part of the document. Our aim is to study the behavior of this test in presence of contamination. The second part which is independent on the first,treats some aspects of ARCH models (autoregressive conditionally heteroscedastic) that are non linear processes. However, since unit root tests and ARCH models are connected, we preferred to present them in a same document.
Autorenporträt
Lynda AtilDoctor at University of Tizi Ouzou,Algeria.She is the author of 5 refereed papers.Her interests are time series,the unit root test,ARCH models,robustness,Bayesian methods.Hocine Fellag,He is professor,the author of 20 papers.He is founder of algerian doctoral school of statistics,honorary professor of Rey Juan Carlos University,Madrid.