This monograph will be of interest to researchers and graduate students in time series and probability.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
EUR 19,90 expédition depuis Allemagne vers France
Destinations, frais et délaisEUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisVendeur : CSG Onlinebuch GMBH, Darmstadt, Allemagne
Gebunden. Etat : 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. N° de réf. du vendeur 18330
Quantité disponible : 1 disponible(s)
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Hardcover. Etat : Like New. Like NewLIKE NEW. book. N° de réf. du vendeur ERICA837038798917X3
Quantité disponible : 1 disponible(s)
Vendeur : ThriftBooks-Atlanta, AUSTELL, GA, Etats-Unis
Hardcover. Etat : Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.13. N° de réf. du vendeur G038798917XI4N10
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Gebunden. Etat : 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. N° de réf. du vendeur 5913570
Quantité disponible : Plus de 20 disponibles
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : 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. N° de réf. du vendeur 9780387989174
Quantité disponible : 2 disponible(s)
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Buch. Etat : 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. N° de réf. du vendeur 9780387989174
Quantité disponible : 2 disponible(s)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9780387989174_new
Quantité disponible : Plus de 20 disponibles
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : 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. N° de réf. du vendeur 9780387989174
Quantité disponible : 1 disponible(s)
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Hardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 583. N° de réf. du vendeur C9780387989174
Quantité disponible : Plus de 20 disponibles
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Feb2215580175568
Quantité disponible : Plus de 20 disponibles