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.
Home page url
Download or read it online for free here:
by 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.
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 Arak M. Mathai, Hans J. Haubold - De Gruyter Open
This is an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and hypothesis testing. Designed for students in engineering and physics.
by R. A. Bailey - Cambridge University Press
This book develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams. The book is ideal for advanced undergraduate and beginning graduate courses.