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
Lectures on Noise Sensitivity and Percolationby Christophe Garban, Jeffrey E. Steif - arXiv
The goal of this set of lectures is to combine two seemingly unrelated topics: (1) The study of Boolean functions, a field particularly active in computer science; (2) Some models in statistical physics, mostly percolation.
(13210 views)
Introduction Probaility and Statisticsby Muhammad El-Taha - University of Southern Maine
Topics: Data Analysis; Probability; Random Variables and Discrete Distributions; Continuous Probability Distributions; Sampling Distributions; Point and Interval Estimation; Large Sample Estimation; Large-Sample Tests of Hypothesis; etc.
(28687 views)
Reversible Markov Chains and Random Walks on Graphsby David Aldous, James Allen Fill - University of California, Berkeley
From the table of contents: General Markov Chains; Reversible Markov Chains; Hitting and Convergence Time, and Flow Rate, Parameters for Reversible Markov Chains; Special Graphs and Trees; Cover Times; Symmetric Graphs and Chains; etc.
(15819 views)
Bayesian Spectrum Analysis and Parameter Estimationby G. Larry Bretthorst - Springer
This work is a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis.
(19172 views)