9781107663916 - probabilistic forecasting and bayesian data assimilation (cambridge texts in applied mathematics) de reich, sebastian (14 resultados)
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Librería: HPB-Red, Dallas, TX, Estados Unidos de AmericaHPB-Red
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paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
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Paperback. Condición: New. In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical example…s designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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Librería: Chiron Media, Wallingford, Reino UnidoChiron Media
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Librería: online-buch-de, Dozwil, Suizaonline-buch-de
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Paperback May 14, 2015. Condición: gebraucht; sehr gut. minimale Standspuren, praktisch ungebraucht.
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Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
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Condición: New. This book covers key ideas and concepts. Ideal introduction for graduate students in any field where Bayesian data assimilation is applied. Num Pages: 306 pages, 70 b/w illus. 7 colour illus. 70 exercises. BIC Classification: PBT; PBW. Category: (P) Professional & Vocational. Dimension: 247 x 175 x 15. Weight in…Grams: 608. . 2015. Paperback. . . . . Books ship from the US and Ireland.
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Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books
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Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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Paperback. Condición: New. In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical example…s designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 136,38
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Condición: New. This book covers key ideas and concepts. Ideal introduction for graduate students in any field where Bayesian data assimilation is applied. Num Pages: 306 pages, 70 b/w illus. 7 colour illus. 70 exercises. BIC Classification: PBT; PBW. Category: (P) Professional & Vocational. Dimension: 247 x 175 x 15. Weight in…Grams: 608. . 2015. Paperback. . . . .
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profus…ion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
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Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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Paperback. Condición: new. Paperback. In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numeri…cal examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas. This book focuses on the Bayesian approach to data assimilation, outlining the subject's key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 68,61
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book focuses on the Bayesian approach to data assimilation, outlining the subject s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for g…raduate students in applied mathematics..
