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
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).
(8548 views)
An Introduction to Stochastic PDEsby Martin Hairer - arXiv
This text is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else.
(8579 views)
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.
(8738 views)
A defense of Columbo: A multilevel introduction to probabilistic reasoningby G. D'Agostini - arXiv
Triggered by a recent interesting article on the too frequent incorrect use of probabilistic evidence in courts, the author introduces the basic concepts of probabilistic inference with a toy model, and discusses several important issues.
(10692 views)