確率・ランダム過程（第４版） Probability and Random Processes （4TH）

確率・ランダム過程（第４版）<br>Probability and Random Processes （4TH）

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確率・ランダム過程（第４版）
Probability and Random Processes （4TH）

Grimmett, Geoffrey/ Stirzaker, David

ウェブストア価格 ¥14,901（本体¥13,547）
Oxford University Press（2020/07発売）
外貨定価 US$ 72.00
ポイント 135pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 688 p.
言語 ENG
商品コード 9780198847595
DDC分類 519.2

Full Description

The fourth edition of this successful text provides an introduction to probability and random processes, with many practical applications. It is aimed at mathematics undergraduates and postgraduates, and has four main aims.

US BL To provide a thorough but straightforward account of basic probability theory, giving the reader a natural feel for the subject unburdened by oppressive technicalities. BE BL To discuss important random processes in depth with many examples.BE BL To cover a range of topics that are significant and interesting but less routine. BE BL To impart to the beginner some flavour of advanced work.BE UE
OP The book begins with the basic ideas common to most undergraduate courses in mathematics, statistics, and science. It ends with material usually found at graduate level, for example, Markov processes, (including Markov chain Monte Carlo), martingales, queues, diffusions, (including stochastic calculus with Itô's formula), renewals, stationary processes (including the ergodic theorem), and option pricing in mathematical finance using the Black-Scholes formula. Further, in this new revised fourth edition, there are sections on coupling from the past, Lévy processes, self-similarity and stability, time changes, and the holding-time/jump-chain construction of continuous-time Markov chains. Finally, the number of exercises and problems has been increased by around 300 to a total of about 1300, and many of the existing exercises have been refreshed by additional parts. The solutions to these exercises and problems can be found in the companion volume, One Thousand Exercises in Probability, third edition, (OUP 2020).CP

1: Events and their probabilities
2: Random variables and their distributions
3: Discrete random variables
4: Continuous random variables
5: Generating functions and their applications
6: Markov chains
7: Convergence of random variables
8: Random processes
9: Stationary processes
10: Renewals
11: Queues
12: Martingales
13: Diffusion processes