Stochastic Modeling of Scientific Data

Peter Guttorp (Autor)

Buch | Softcover

384 Seiten

2020
Chapman & Hall/CRC (Verlag)
978-0-367-44900-1 (ISBN)

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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.

Guttorp, Peter

Table of contents; Discrete time Markov chains; Continuous time Markov chains; Markov random fields; Point processes; Brownian motion and diffusion; Appendix 1: Statistical theory for the multinomial distribution; Appendix 2: Linear difference equations with constant coefficients; Appendix 3: Some theory of partial differential equations.

Erscheinungsdatum	16.01.2021
Sprache	englisch
Maße	156 x 234 mm
Gewicht	453 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Themenwelt	Naturwissenschaften ► Biologie
ISBN-10	0-367-44900-5 / 0367449005
ISBN-13	978-0-367-44900-1 / 9780367449001
Zustand	Neuware