Springer, 672 pages, 2010. This book is a comprehensive treatment
of inference for hidden Markov models, including both algorithms
and statistical theory.
Olivier Cappe, Eric Moulines, Tobias Ryden. Inference in Hidden Markov Models
- формат pdf
- размер 6.06 МБ
- добавлен 17 ноября 2011 г.
Смотрите также
Bickel P.J., Doksum K.A. Mathematical Statistics: Basic Ideas and Selected Topics. Volume 1
- формат djvu
- размер 17.63 МБ
- добавлен 30 апреля 2011 г.
Prentice Hall, 2001. - 679 Pages. This classic, time-honored introduction to the theory and practice of statistics modeling and inference reflects the changing focus of contemporary Statistics. Coverage begins with the more general nonparametric point of view and then looks at parametric models as submodels of the nonparametric ones which can be described smoothly by Euclidean parameters. Although some computational issues are discussed, this is...
Davison A.C. Statistical Models
- формат pdf
- размер 5.05 МБ
- добавлен 15 октября 2011 г.
Cambridge University Press, 2008. - 738 pages. Models and likelihood are the backbone of modern statistics and data analysis. The coverage is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics. Anthony...
DeGroot M.H., Schervish M.J. Probability and Statistics
- формат pdf
- размер 6.13 МБ
- добавлен 04 октября 2011 г.
Addison Wesley, 2011. - 911 pages. 4th Edition The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors a...
DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics
- формат pdf
- размер 28.11 МБ
- добавлен 06 сентября 2011 г.
Addison-wesley publishing company September 1989 730 pages Probability & Statistics was written for a one or two semester probability and statistics course offered primarily at four-year institutions and taken mostly by sophomore and junior level students, majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus. The revision of this wel...
Koller D., Friedman N. Probabilistic Graphical Models: Principles and Techniques
- формат pdf
- размер 66.17 МБ
- добавлен 22 мая 2011 г.
The MIT Press, 2009. - 1208 pages. Most tasks require a person or an automated system to reason—to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, all...
Rebai A. (ed.) Bayesian Network
- формат pdf
- размер 22.62 МБ
- добавлен 30 сентября 2011 г.
Издательство InTech, 2010, -442 pp. Bayesian networks are graphical models that represent the probabilistic relationships among a large number of variables and perform probabilistic inference with those variables. They constitute a formal framework for the representation and communication of decisions resulting from reasoning under uncertainty. Bayesian networks, which were named after Thomas Bayes (1702-1761), one of the founders of the probab...
Sheldon M. Introduction to Probability Models
- формат pdf
- размер 3.17 МБ
- добавлен 29 июня 2011 г.
Book 2007, 782p, ISBN-13: 978-0-12-598062-3 Ninth Edition content Introduction to Probability Theory Introduction to Probability Theory Conditional Probability and Conditional Expectation Markov Chains The Exponential Distribution and the Poisson Process Continuous-Time Markov Chains Renewal Theory and Its Applications Queueing Theory Reliability Theory Brownian Motion and Stationary Processes Simulation Appendix: Solutions to Starred Exercises
Stroock D.W. An Introduction to Markov Processes
- формат pdf
- размер 7.73 МБ
- добавлен 22 января 2012 г.
Учебник, Springer 1st edition (2005), 185 pages. This book is based on the lectures given by the author at the Massachusetts Institute of Technology to a mixed audience consisting not only of mathematicians, but also of students interested in concrete applications of the theory of Markov processes. This explains the choice of the presentation level, which is deemed accessible to non-mathematicians as well as to mathematicians.
Tavar? S., Zeitouni O. Lectures on Probability Theory and Statistics
- формат pdf
- размер 2.12 МБ
- добавлен 04 января 2011 г.
Springer, 2008. - 315 pages. This volume contains lectures given at the 31st Probability Summer School in Saint-Flour (July 8-25, 2001). Simon Tavar?’s lectures serve as an introduction to the coalescent, and to inference for ancestral processes in population genetics. The stochastic computation methods described include rejection methods, importance sampling, Markov chain Monte Carlo, and approximate Bayesian methods. Ofer Zeitouni’s course on...
Young G.A., Smith R.L., Essentials of Statistical Inference
- формат pdf
- размер 2.91 МБ
- добавлен 17 ноября 2011 г.
Cambridge University Press, 236 pages, 2010. This engaging textbook introduces the key ideas behind drawing formal inferences from data. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it is a concise account of the main approaches to inference, with particular emphasis on the contrasts between them.