Stochastic Modeling of Scientific Data (Paperback)

Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields and hidden Markov models in a clear, thoughtful and succinct manner. The distinguishing feature of this work is that, in addition to probability theory, it contains statistical aspects of model fitting and a variety of data sets that are either analyzed in the text or used as exercises. Markov chain Monte Carlo methods are introduced for evaluating likelihoods in complicated models and the forward backward algorithm for analyzing hidden Markov models is presented. The strength of this text lies in the use of informal language that makes the topic more accessible to non-mathematicians. The combinations of hard science topics with stochastic processes and their statistical inference puts it in a new category of probability textbooks. The numerous examples and exercises are drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics.

General

Imprint:	Crc Press
Country of origin:	United Kingdom
Release date:	December 2020
First published:	1995
Authors:	Peter Guttorp
Dimensions:	234 x 156mm (L x W)
Format:	Paperback
Pages:	384
ISBN-13:	978-0-367-44900-1
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Biology, life sciences > General Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics Promotions
LSN:	0-367-44900-5
Barcode:	9780367449001

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