Authors:Bani K. Mallick, David Gold, Veera Baladandayuthapan
Publisher: Wiley
Keywords: statistics, practice, data, expression, analysis, gene, bayesian
Number of Pages: 252
Published: 2009-09-15
List price: $90.00
ISBN-10: 0470517662
ISBN-13: 9780470517666
The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinformatics. This book is devoted exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing Bioinformatics. Case studies, illustrating Bayesian analyses of public gene expression data, provide the backdrop for students to develop analytical skills, while the mo
Author: Martin Pelikan
Publisher: Springer
Keywords: studies, algorithms, fuzziness, soft, computing, evolutionary, generation, bayesian, optimization, algorithm, new, hierarchical
Number of Pages: 166
Published: 2005-03-24
List price: $189.00
ISBN-10: 3540237747
ISBN-13: 9783540237747
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA) . They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, moti
Authors:Jayanta K. Ghosh, Mohan Delampady, Tapas Samanta,
Publisher: Springer
Keywords: springer, texts, statistics, methods, theory, bayesian, analysis, introduction
Number of Pages: 352
Published: 2006-07-27
List price: $99.00
ISBN-10: 0387400842
ISBN-13: 9780387400846
This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing. Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques. Many topics are at the cutt
Authors:Nils Lid Hjort, Chris Holmes, Peter Müller, Stephen G
Publisher: Cambridge University Press
Keywords: probabilistic, mathematics, statistical, series, nonparametrics, cambridge, bayesian
Number of Pages: 312
Published: 2010-04-12
List price: $59.00
ISBN-10: 0521513464
ISBN-13: 9780521513463
Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount of data. Computational issues, though challenging, are no longer intractable. All that is needed is an entry point: this intelligent book is the perfect guide to what can seem a forbidding landscape. Tutorial chapters by Ghosal, Lijoi and Prünster, Teh and Jordan, and Dunson advance from theory, to basic models and hierarchical modeling, to applications and implementation, particularly in computer science and biostatistics. These are c
Authors:Andrew Gelman, John B. Carlin, Hal S. Stern, Donal
Publisher: Chapman & Hall
Keywords: crc, texts, statistical, science, hall, chapman, data, analysis, second, bayesian
Number of Pages: 696
Published: 2003-07-29
List price: $73.95
ISBN-10: 158488388X
ISBN-13: 9781584883883
Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: ·Stronger focus on MCMC·Revision of the computational advice in Part III·New chapter
Authors:Kenji Doya, Shin Ishii, Alexandre Pouget, Rajesh P. N
Publisher: The MIT Press
Keywords: coding, computational, neuroscience, neural, approaches, brain, probabilistic, bayesian
Number of Pages: 340
Published: 2007-01-01
List price: $55.00
ISBN-10: 026204238X
ISBN-13: 9780262042383
A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering experimental data. Bayesian Brain brings together contributions from both experimental and theoretical neuroscientists that examine the brain mechanisms of perception, decision making, and motor control according to the concepts of Bayesian estimation. After a
Author: Stuart A. Klugman
Publisher: Springer
Keywords: risk, series, insurance, economic, security, international, huebner, actuarial, statistics, science, emphasis, credibility, bayesian
Number of Pages: 256
Published: 1991-11-30
List price: $185.00
ISBN-10: 0792392124
ISBN-13: 9780792392125
