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Stochastic Modeling of Scientific Data (Chapman & Hall/CRC Texts in Statistical Science) by Guttorp, Peter is a nonfiction available to read on EtoBox.

What is Stochastic Modeling of Scientific Data (Chapman & Hall/CRC Texts in Statistical Science) about?

This text 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 main 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 analysed 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 analysing hidden Markov models is presented. The numerous examples and exercises drawn from astronomy, geology, genetics, hydrology, neurophysiology and physics, make this an ideal textbook for researchers, neurophysiology and physics, make this an ideal textbook for researchers, lecturers and graduate students studying statistics and probability, especially applied probability and stochastic processes. Read more... Abstract: This text combines stochastic modeling and statistical inference in a variety of standard and less common models, such as point processes, Markov random fields

Who reads Stochastic Modeling of Scientific Data (Chapman & Hall/CRC Texts in Statistical Science)?

Author

Guttorp, Peter

Publisher

Chapman and Hall/CRC

Published

1995

Language

EN

ISBN

9781351413664

Category

nonfiction

Subjects

Mathematics, Stem