Stochastic Modeling of Scientific Data by Peter GuttorpStochastic Modeling of Scientific Data by Peter Guttorp

Stochastic Modeling of Scientific Data

byPeter Guttorp, Vladimir N. MininEditorPeter Guttorp

Hardcover | August 1, 1995

Pricing and Purchase Info

$222.50 online 
$237.90 list price save 6%
Earn 1,113 plum® points

Prices and offers may vary in store


In stock online

Ships free on orders over $25

Not available in stores


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.
Title:Stochastic Modeling of Scientific DataFormat:HardcoverDimensions:384 pages, 9.21 × 6.14 × 1.1 inPublished:August 1, 1995Publisher:Taylor and Francis

The following ISBNs are associated with this title:

ISBN - 10:0412992817

ISBN - 13:9780412992810


Editorial Reviews

"The author's lucid presentation of his material together with this very great number of applications from life sciences, make this an excellent buy for only thirty pounds for every biometrician." -Biometrics "When it comes to introducing Markov chains, everyone talks about the weather but nobody does anything about getting real data. In this book, though, we get not only the pattern of rainfall in Snoqualmie Falls, Washington, but wind directions in South Africa, and interarrival times of cyclones in the bay of Bengal. The objecive is to provide an introduction to stochastic processes suited to those who while not necessarily shy of mathematics, are primarily interested in problems with the flavor of real life...still, even hard-bitten mathematical probabilists may find new insights in this insistently realistic approach." -Zentralblatt fur Mathematik