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Time Series Analysis of Long Memory versus Structural Breaks - A Time-Varying Memory Approach - Goerg, Georg M.
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
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Goerg, Georg M.:
Time Series Analysis of Long Memory versus Structural Breaks - A Time-Varying Memory Approach - Taschenbuch

2010, ISBN: 9783639246018

[ED: Taschenbuch / Paperback], [PU: 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., DE, [SC: 0.00], Neuware, gewerbliches Angebot, H: 220mm, B: 150mm, T: 6mm, 120, [GW: 175g], Selbstabholung und Barzahlung, PayPal, offene Rechnung, Banküberweisung, Interntationaler Versand

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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

ISBN: 9783639246018

[ED: Taschenbuch], [PU: VDM Verlag], 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., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 220x150x7 mm, 120, [GW: 195g], PayPal, offene Rechnung, Banküberweisung, De internationale scheepvaart

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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 - neues Buch

ISBN: 9783639246018

ID: eb191a30cf4eefae0198751b9f65e5bb

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 (Paperback) - Georg M Goerg
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Georg M Goerg:
Time Series Analysis of Long Memory Versus Structural Breaks (Paperback) - Taschenbuch

2010, ISBN: 3639246012

ID: 19771986246

[EAN: 9783639246018], Nieuw boek, [SC: 1.14], [PU: VDM Verlag, Germany], Language: English . Brand New Book. 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.

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Time Series Analysis of Long Memory versus Structural Breaks - Georg M. Goerg
Vergriffenes Buch, derzeit bei uns nicht verfügbar.
(*)
Georg M. Goerg:
Time Series Analysis of Long Memory versus Structural Breaks - Taschenbuch

2010, ISBN: 3639246012

ID: 19725764441

[EAN: 9783639246018], Nieuw boek, [SC: 20.26], [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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Details zum Buch
Time Series Analysis of Long Memory versus Structural Breaks: A Time-Varying Memory Approach

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 17.08.2017 12:56:09
ISBN/EAN: 9783639246018

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


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