Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with Mathematica® Support - Rilegato

Gregory, Phil

Rilegato

ISBN 10: 052184150X ISBN 13: 9780521841504

Casa editrice: Cambridge University Press, 2005

Riassunto

Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125.

Su questo libro

Recensione:

'As well as the usual topics to be found in a text on Bayesian inference, chapters are included on frequentist inference (for contrast), non-linear model fitting, spectral analysis and Poisson sampling.' Zentralblatt MATH

'The examples are well integrated with the text and are enlightening.' Contemporary Physics

'The book can easily keep the readers amazed and attracted to its content throughout the read and make them want to return back to it recursively. It presents a perfect balance between theoretical inference and a practical know-how approach to Bayesian methods.' Stan Lipovetsky, Technometrics

Descrizione del libro:

Increasingly, researchers in many branches of science are coming into contact with Bayesian statistics or Bayesian probability theory. This book provides a clear exposition of the underlying concepts with large numbers of worked examples and problem sets. Background material is provided in appendices and supporting Mathematica® notebooks are available.

Su questa edizione

• Editore: Cambridge University Press
• Data di pubblicazione: 2005
• ISBN 10: 052184150X
• ISBN 13: 9780521841504
• Rilegatura: Copertina rigida
• Numero di pagine: 488