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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics) - Tapa dura
Sinopsis
The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.
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Críticas
From the reviews:
SHORT BOOK REVIEWS
"...will make this book useful as a reference source to the more theoretical among time series specialists."
ZENTRALBLATT MATH
"This publication can be recommended to readers familiar with the basic concepts of time series who are interested in estimation problems in nonminimum phase processes."
Reseña del editor
The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.
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- EditorialSpringer
- Año de publicación1999
- ISBN 10 038798917X
- ISBN 13 9780387989174
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de páginas268
- Contacto del fabricanteno disponible
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Gaussian and Non-Gaussian Linear Time Series and Random Fields.
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New York, NY, U.S.A. Springer Verlag, 1999
ISBN 10: 038798917X
ISBN 13: 9780387989174
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Librería: CSG Onlinebuch GMBH, Darmstadt, Alemania
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Gebunden. Condición: Sehr gut. Gebraucht - Sehr gut Zustand: Sehr gut, XIII, 246 pp. About this book The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book. Written for researchers, graduate students. Nº de ref. del artículo: 18330
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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)
Librería: Mispah books, Redhill, SURRE, Reino Unido
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Hardcover. Condición: Like New. Like NewLIKE NEW. book. Nº de ref. del artículo: ERICA837038798917X3
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.13. Nº de ref. del artículo: G038798917XI4N10
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
Impresión bajo demandaLibrería: moluna, Greven, Alemania
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gau. Nº de ref. del artículo: 5913570
Cantidad disponible: Más de 20 disponibles
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
Publicado por
Springer New York Dez 1999, 1999
ISBN 10: 038798917X
ISBN 13: 9780387989174
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book is concerned with linear time series and random fields in both the Gaussian and especially the non-Gaussian context. The principal focus is on autoregressive moving average models and analogous random fields. Probabilistic and statistical questions are both discussed. The Gaussian models are contrasted with noncausal or noninvertible (nonminimum phase) non-Gaussian models which can have a much richer structure than Gaussian models. The book deals with problems of prediction (which can have a nonlinear character) and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. The book is intended as a text for graduate students in statistics, mathematics, engineering, the natural sciences and economics. An initial background in probability theory and statistics is suggested. Notes on background, history and open problems are given at the end of the book. 268 pp. Englisch. Nº de ref. del artículo: 9780387989174
Cantidad disponible: 2 disponibles
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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. In. Nº de ref. del artículo: ria9780387989174_new
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
Publicado por
Springer New York, Springer US, 1999
ISBN 10: 038798917X
ISBN 13: 9780387989174
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Much of this book is concerned with autoregressive and moving av erage linear stationary sequences and random fields. These models are part of the classical literature in time series analysis, particularly in the Gaussian case. There is a large literature on probabilistic and statistical aspects of these models-to a great extent in the Gaussian context. In the Gaussian case best predictors are linear and there is an extensive study of the asymptotics of asymptotically optimal esti mators. Some discussion of these classical results is given to provide a contrast with what may occur in the non-Gaussian case. There the prediction problem may be nonlinear and problems of estima tion can have a certain complexity due to the richer structure that non-Gaussian models may have. Gaussian stationary sequences have a reversible probability struc ture, that is, the probability structure with time increasing in the usual manner is the same as that with time reversed. Chapter 1 considers the question of reversibility for linear stationary sequences and gives necessary and sufficient conditions for the reversibility. A neat result of Breidt and Davis on reversibility is presented. A sim ple but elegant result of Cheng is also given that specifies conditions for the identifiability of the filter coefficients that specify a linear non-Gaussian random field. Nº de ref. del artículo: 9780387989174
Cantidad disponible: 1 disponibles
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
Publicado por
Springer New York, Springer US Dez 1999, 1999
ISBN 10: 038798917X
ISBN 13: 9780387989174
Nuevo
Tapa dura
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Neuware -Much of this book is concerned with autoregressive and moving av erage linear stationary sequences and random fields. These models are part of the classical literature in time series analysis, particularly in the Gaussian case. There is a large literature on probabilistic and statistical aspects of these models-to a great extent in the Gaussian context. In the Gaussian case best predictors are linear and there is an extensive study of the asymptotics of asymptotically optimal esti mators. Some discussion of these classical results is given to provide a contrast with what may occur in the non-Gaussian case. There the prediction problem may be nonlinear and problems of estima tion can have a certain complexity due to the richer structure that non-Gaussian models may have. Gaussian stationary sequences have a reversible probability struc ture, that is, the probability structure with time increasing in the usual manner is the same as that with time reversed. Chapter 1 considers the question of reversibility for linear stationary sequences and gives necessary and sufficient conditions for the reversibility. A neat result of Breidt and Davis on reversibility is presented. A sim ple but elegant result of Cheng is also given that specifies conditions for the identifiability of the filter coefficients that specify a linear non-Gaussian random field.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch. Nº de ref. del artículo: 9780387989174
Cantidad disponible: 2 disponibles
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
Publicado por
Springer-Verlag New York Inc., 1999
ISBN 10: 038798917X
ISBN 13: 9780387989174
Nuevo
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Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 583. Nº de ref. del artículo: C9780387989174
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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: ABLIING23Feb2215580175568
Cantidad disponible: Más de 20 disponibles