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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics) - Hardcover
Inhaltsangabe
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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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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Gaussian and Non-Gaussian Linear Time Series and Random Fields.
Verlag:
New York, NY, U.S.A. Springer Verlag, 1999
ISBN 10: 038798917X
ISBN 13: 9780387989174
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Gebunden. Zustand: 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. Bestandsnummer des Verkäufers 18330
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Hardcover. Zustand: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.13. Bestandsnummer des Verkäufers G038798917XI4N10
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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)
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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Gaussian and Non-Gaussian Linear Time Series and Random Fields
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Buch. Zustand: 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. Bestandsnummer des Verkäufers 9780387989174
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