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
Markov Chains and Stochastic Stabilityby S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
(22016 views)
Topics in Random Matrix Theoryby Terence Tao
This is a textbook for a graduate course on random matrix theory, inspired by recent developments in the subject. This text focuses on foundational topics in random matrix theory upon which the most recent work has been based.
(14392 views)
CK-12 Basic Probability and Statistics: A Short Courseby Brenda Meery - CK-12.org
CK-12 Foundation's Basic Probability and Statistics– A Short Course is an introduction to theoretical probability and data organization. Students learn about events, conditions, random variables, and graphs and tables that allow them to manage data.
(21060 views)
Basic Data Analysis and More: A Guided Tour Using Pythonby 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).
(15099 views)