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Probabilistic Forecasting and Bayesian Data Assimilation (Paperback) Loot Price: R1,386
Discovery Miles 13 860
Probabilistic Forecasting and Bayesian Data Assimilation (Paperback): Sebastian Reich, Colin Cotter

Probabilistic Forecasting and Bayesian Data Assimilation (Paperback)

Sebastian Reich, Colin Cotter

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Loot Price R1,386 Discovery Miles 13 860 | Repayment Terms: R130 pm x 12*

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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 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.

General

Imprint: Cambridge UniversityPress
Country of origin: United Kingdom
Release date: May 2015
Authors: Sebastian Reich • Colin Cotter
Dimensions: 244 x 170 x 16mm (L x W x T)
Format: Paperback - Trade
Pages: 308
ISBN-13: 978-1-107-66391-6
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Science & Mathematics > Mathematics > Applied mathematics > General
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LSN: 1-107-66391-1
Barcode: 9781107663916

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