Markov Chains and Stochastic Stability
by S.P. Meyn, R.L. Tweedie
Publisher: Springer 2005
Number of pages: 567
This book describes the modern theory of general state space Markov chains, and the application of that theory to operations research, time series analysis, and systems and control theory. It is intended as an advanced graduate text in any of these areas, as well as being a research monograph incorporating a new and thorough treatment of the stability of general Markov chains. Many of the theoretical results appear here for the first time, and much of the theory and the models which are used to illustrate the theory, and to provide extensions of the theory in special cases, have not previously been brought together in book form. This book thus provides a readable account of the development over the last two decades of a fundamental and applicable area of stochastic processes, and as such will be of value not only in probability theory but in the many discplines where these models form the basis of analysis.
Home page url
Download or read it online for free here:
by David Blackwell, at al. - IMS
The bulk of the articles in this volume are research articles in probability, statistics, gambling, game theory, Markov decision processes, set theory and logic, comparison of experiments, games of timing, merging of opinions, etc.
by O. Melchert - arXiv
In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments).
by Pavel Bleher, Alexander Its - Cambridge University Press
The book covers broad areas such as topologic and combinatorial aspects of random matrix theory; scaling limits, universalities and phase transitions in matrix models; universalities for random polynomials; and applications to integrable systems.
by Albert Tarantola - SIAM
The first part deals with discrete inverse problems with a finite number of parameters, while the second part deals with general inverse problems. The book for scientists and applied mathematicians facing the interpretation of experimental data.