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Time Series Analysis of Long Memory versus Structural Breaks: A Time-Varying Memory Approach - Georg M. Goerg
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Time Series Analysis of Long Memory versus Structural Breaks: A Time-Varying Memory Approach - Taschenbuch

ISBN: 3639246012

[SR: 7195225], Paperback, [EAN: 9783639246018], VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, Book, [PU: VDM Verlag Dr. Müller], VDM Verlag Dr. Müller, Several real world processes exhibit a very slowly decaying dependence over time, e.g. river flow data, tree ring width data, or stock volatility. In the time series literature this phenomenon is known as long memory or long range dependence. An alternative view are structural breaks occurring over time that make the process appear to have long memory, but in fact it does not. This work gives a brief introduction to univariate time series analysis and then studies the long memory versus structural breaks debate. A detailed study of an error duration model gives a nice view of stochastic processes in general and sheds new light on the aforementioned controversy. After presenting various estimators and tests for long range dependence, a chapter with applications compares short and long memory models for financial data. The contribution of this work is a model for time-varying (long) memory and herewith tries to unify the concurring views of long memory and structural breaks. This book is intended for readers interested in applied math and statistics, in particular time series analysis., 13983, Probability & Statistics, 226699, Applied, 13884, Mathematics, 75, Science & Math, 1000, Subjects, 283155, Books, 491548, Statistics, 468218, Mathematics, 468216, Science & Mathematics, 465600, New, Used & Rental Textbooks, 2349030011, Specialty Boutique, 283155, Books

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Several real world processes exhibit a very slowly decaying dependence over time, e.g. river flow data, tree ring width data, or stock volatility. In the time series literature this phenomenon is known as long memory or long range dependence. An alternative view are structural breaks occurring over time that make the process appear to have long memory, but in fact it does not. This work gives a brief introduction to univariate time series analysis and then studies the long memory versus structural breaks debate. A detailed study of an error duration model gives a nice view of stochastic processes in general and sheds new light on the aforementioned controversy. After presenting various estimators and tests for long range dependence, a chapter with applications compares short and long memory models for financial data. The contribution of this work is a model for time-varying (long) memory and herewith tries to unify the concurring views of long memory and structural breaks. This book is intended for readers interested in applied math and statistics, in particular time series analysis. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Mathematik / Stochastik & Statistik, [PU: VDM Verlag Dr. Müller, Saarbrücken]

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Time Series Analysis of Long Memory versus Structural Breaks - Georg M. Goerg
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Georg M. Goerg:
Time Series Analysis of Long Memory versus Structural Breaks - Taschenbuch

2010

ISBN: 3639246012

ID: 19725730213

[EAN: 9783639246018], Neubuch, [PU: VDM Verlag Mrz 2010], Neuware - Several real world processes exhibit a very slowly decaying dependence over time, e.g. river flow data, tree ring width data, or stock volatility. In the time series literature this phenomenon is known as long memory or long range dependence. An alternative view are structural breaks occurring over time that make the process appear to have long memory, but in fact it does not. This work gives a brief introduction to univariate time series analysis and then studies the long memory versus structural breaks debate. A detailed study of an error duration model gives a nice view of stochastic processes in general and sheds new light on the aforementioned controversy. After presenting various estimators and tests for long range dependence, a chapter with applications compares short and long memory models for financial data. The contribution of this work is a model for time-varying (long) memory and herewith tries to unify the concurring views of long memory and structural breaks. This book is intended for readers interested in applied math and statistics, in particular time series analysis. 120 pp. Englisch

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Georg M. Goerg:
Time Series Analysis of Long Memory versus Structural Breaks: A Time-Varying Memory Approach - Taschenbuch

ISBN: 3639246012

Taschenbuch, [EAN: 9783639246018], VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, Book, [PU: VDM Verlag Dr. Müller], VDM Verlag Dr. Müller, 56254011, Wahrscheinlichkeit & Statistik, 56248011, Angewandte Mathematik, 56214011, Mathematik, 56047011, Wissenschaft, 54071011, Genres, 52044011, Fremdsprachige Bücher

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Time Series Analysis of Long Memory versus Structural Breaks: A Time-Varying Memory Approach
Autor:

Goerg, Georg M.

Titel:

Time Series Analysis of Long Memory versus Structural Breaks: A Time-Varying Memory Approach

ISBN-Nummer:

3639246012

Several real world processes exhibit a very slowly decaying dependence over time, e.g. river flow data, tree ring width data, or stock volatility. In the time series literature this phenomenon is known as long memory or long range dependence. An alternative view are structural breaks occurring over time that make the process appear to have long memory, but in fact it does not. This work gives a brief introduction to univariate time series analysis and then studies the long memory versus structural breaks debate. A detailed study of an error duration model gives a nice view of stochastic processes in general and sheds new light on the aforementioned controversy. After presenting various estimators and tests for long range dependence, a chapter with applications compares short and long memory models for financial data. The contribution of this work is a model for time-varying (long) memory and herewith tries to unify the concurring views of long memory and structural breaks. This book is intended for readers interested in applied math and statistics, in particular time series analysis.

Detailangaben zum Buch - Time Series Analysis of Long Memory versus Structural Breaks: A Time-Varying Memory Approach


EAN (ISBN-13): 9783639246018
ISBN (ISBN-10): 3639246012
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: VDM Verlag Dr. Mueller Akt.ges.&Co.KG

Buch in der Datenbank seit 11.08.2008 19:24:34
Buch zuletzt gefunden am 11.01.2017 12:20:59
ISBN/EAN: 3639246012

ISBN - alternative Schreibweisen:
3-639-24601-2, 978-3-639-24601-8

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