Convergence of Stochastic Processes
by D. Pollard
Publisher: Springer 1984
ISBN/ASIN: 1461297583
ISBN-13: 9781461297581
Number of pages: 223
Description:
An exposition od selected parts of empirical process theory, with related interesting facts about weak convergence, and applications to mathematical statistics. The high points of the book describe the combinatorial ideas needed to prove maximal inequalities for empirical processes indexed by classes of sets or classes of functions.
Download or read it online for free here:
Download link
(8.6MB, PDF)
Similar books
Principles of Data Analysisby Cappella Archive - Prasenjit Saha
This is a short book about the principles of data analysis. The emphasis is on why things are done rather than on exactly how to do them. If you already know something about the subject, then working through this book will deepen your understanding.
(15740 views)
Statistics, Probability, and Game Theory: papers in honor of David Blackwellby 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.
(14619 views)
Seeing Theory: A visual introduction to probability and statisticsby T. Devlin, J. Guo, D. Kunin, D. Xiang - Brown University
The intent of the website and these notes is to provide an intuitive supplement to an introductory level probability and statistics course. The level is also aimed at students who are returning to the subject and would like a concise refresher ...
(9587 views)
Markov Chains and Mixing Timesby D. A. Levin, Y. Peres, E. L. Wilmer - American Mathematical Society
An introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate of convergence of a Markov chain to the stationary distribution as a function of the size and geometry of the state space.
(15387 views)