Convergence of Stochastic Processes
by D. Pollard
Publisher: Springer 1984
Number of pages: 223
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.
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by Alexander K. Hartmann - arXiv
This is a practical introduction to randomness and data analysis, in particular in the context of computer simulations. At the beginning, the most basics concepts of probability are given, in particular discrete and continuous random variables.
This book is developed as a free, collaborative and interactive learning environment for elementary probability and statistics education. The book blends information technology, scientific techniques and modern pedagogical concepts.
by 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 ...
by Luc Devroye - Springer
The book on small field on the crossroads of statistics, operations research and computer science. The applications of random number generators are wide and varied. The study of non-uniform random variates is precisely the subject area of the book.