Probability theory / A. Alexandr. Borovkov ; Edited by K. A. Borovkov ; translated by O.B. Borovkova and P.S. Ruzankin
Type de document : Livre numériqueCollection : UniversitextLangue : anglais.Éditeur : New York : Springer, 2013ISBN: 9781447152019.ISSN: 2191-6675.Sujet MSC : 60-01, Introductory exposition (textbooks, tutorial papers, etc.) pertaining to probability theory60A05, Foundations of probability theory, Axioms; other general questions in probability
60F05, Limit theorems in probability theory, Central limit and other weak theorems
60F10, Limit theorems in probability theory, Large deviationsEn-ligne : Springerlink | Zentralblatt | MathSciNet
This is the English translation of the 5th revised and extended edition of A. A. Borovkov’s book published in 2009 in Russian. ... After a classical introduction to probability theory in the spirit of A. N. Kolmogorov’s “Grundbegriffe” (Chapters 1–8), the author offers a profound and extensive treatment of random processes in discrete time, starting with the classical limit theorems for i.i.d. sequences of random variables and a newly written chapter on their large deviation theory. These are followed by chapters on renewal processes, on zero-one laws for random walks and an updated treatment of their factorization identities. The ergodic theory of Markov chains and the convergence theorems for discrete martingales pave the way for two chapters on the ergodic theory of general stationary sequences and on stochastic recursive sequences. The last five chapters focus on continuous time processes, such as Brownian motion and Lévy processes, and the connection between discrete and continuous time processes via functional limit theorems. The last two chapters introduce general Markov processes in discrete space and Gaussian processes. Three newly added appendices on regularly varying functions, convergence theorems to stable laws as well as on distribution bounds for the sums of i.i.d. sequences round off this monumental work.
Given the amount of the material, the book may well serve as the basis of up to four consecutive, mainly undergraduate probability courses.
Although in the last years many new topics in probability theory have gained a lot of attention, the present author’s account is a precious self-contained standard reference, which preserves and prolongs the excellence of the Soviet probability education to our days. (Zentralblatt)
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