An Introduction To Probability And Stochastic Processes

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An Introduction to Probability and Stochastic Processes

An Introduction to Probability and Stochastic Processes
Author :
Publisher : Springer Science & Business Media
Total Pages : 228
Release :
ISBN-10 : 9781461227267
ISBN-13 : 1461227267
Rating : 4/5 (267 Downloads)

Book Synopsis An Introduction to Probability and Stochastic Processes by : Marc A. Berger

Download or read book An Introduction to Probability and Stochastic Processes written by Marc A. Berger and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: These notes were written as a result of my having taught a "nonmeasure theoretic" course in probability and stochastic processes a few times at the Weizmann Institute in Israel. I have tried to follow two principles. The first is to prove things "probabilistically" whenever possible without recourse to other branches of mathematics and in a notation that is as "probabilistic" as possible. Thus, for example, the asymptotics of pn for large n, where P is a stochastic matrix, is developed in Section V by using passage probabilities and hitting times rather than, say, pulling in Perron Frobenius theory or spectral analysis. Similarly in Section II the joint normal distribution is studied through conditional expectation rather than quadratic forms. The second principle I have tried to follow is to only prove results in their simple forms and to try to eliminate any minor technical com putations from proofs, so as to expose the most important steps. Steps in proofs or derivations that involve algebra or basic calculus are not shown; only steps involving, say, the use of independence or a dominated convergence argument or an assumptjon in a theorem are displayed. For example, in proving inversion formulas for characteristic functions I omit steps involving evaluation of basic trigonometric integrals and display details only where use is made of Fubini's Theorem or the Dominated Convergence Theorem.


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