发帖
雷达卡
Chapter 1 reviews elementary probability and provides a brief survey of relevant results from measure theory. Chapter 2 is an extended essay on calculating expectations. Chapter 3 deals with probabilistic applications of convexity, inequalities, and optimization theory. Chapters 4 and 5 touch on combinatorics and combinatorial optimization. Chapters 6 through 11 present core material on stochastic processes. If supplemented with appropriate sections from Chapters 1 and 2, there is sufficient material for a traditional semester-long course in stochastic processes covering the basics of Poisson processes, Markov chains, branching processes, martingales, and diffusion processes. The second edition adds two new chapters on asymptotic and numerical methods and an appendix that separates some of the more delicate mathematical theory from the steady flow of examples in the main text.
Besides the two new chapters, the second edition includes a more extensive list of exercises, many additions to the exposition of combinatorics, new material on rates of convergence to equilibrium in reversible Markov chains, a discussion of basic reproduction numbers in population modeling, and better coverage of Brownian motion. Because many chapters are nearly self-contained, mathematical scientists from a variety of backgrounds will find Applied Probability useful as a reference
本帖隐藏的内容
Applied Probability.pdf
(4.3 MB, 需要: 10 个论坛币)
Product Details
- Series: Springer Texts in Statistics
- Hardcover: 436 pages
- Publisher: Springer; 2nd ed. 2010 edition (August 31, 2010)
- Language: English
- ISBN-10: 9781441971647
- ISBN-13: 978-1441971647
- ASIN: 1441971645
- Product Dimensions: 6.1 x 1 x 9.2 inches
- Shipping Weight: 1.8 pounds (View shipping rates and policies)
- Average Customer Review: 4.7 out of 5 stars See all reviews(3 customer reviews)
京公网安备 11010802022788号
