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應(yīng)用隨機過程：概率模型導論（英文版＂第11版）

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本文關(guān)鍵詞：應(yīng)用隨機過程

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Preface 閱讀

Introduction to Probability Theory 閱讀

Random Variables

2.6.1　The Joint Distribution of the Sample Mean and Sample Variance from a Normal Population

Conditional Probability and Conditional Expectation

3.4.1　Computing Variances by Conditioning

3.5　Computing Probabilities by Conditioning

3.6　Some Applications

3.6.1　A List Model

3.6.2　A Random Graph

3.7　An Identity for Compound Random Variables

Exercises

Markov Chains

4.4.1　Limiting Probabilities

4.5　Some Applications

4.11.1　Predicting the States

Exercises　

References

The Exponential Distribution and the Poisson Process

Continuous-Time Markov Chains

Renewal Theory and Its Applications　

7.5.1　Alternating Renewal Processes

Queueing Theory

8.1　Introduction

8.2　Preliminaries

8.2.1　Cost Equations

8.2.2　Steady-State Probabilities

8.3　Exponential Models

8.4　Network of Queues　

8.4.1　Open Systems

8.4.2　Closed Systems

8.7.1　The G / M / 1 Busy and Idle Periods　

Reliability Theory

9.1　Introduction　

9.2　Structure Functions　

9.2.1　Minimal Path and Minimal Cut Sets

9.3　Reliability of Systems of Independent Components

9.4　Bounds on the Reliability Function

9.4.1　Method of Inclusion and Exclusion

9.4.2　Second Method for Obtaining Bounds on r (p)　

9.5　System Life as a Function of Component Lives

9.6　Expected System Lifetime　

9.6.1　An Upper Bound on the Expected Life of a Parallel System

9.7　Systems with Repair

9.7.1　A Series Model with Suspended Animation

Exercises

References

Brownian Motion and Stationary Processes　

10.3.1　Brownian Motion with Drift

10.3.2　Geometric Brownian Motion

10.4　Pricing Stock Options

Simulation

11.4.1　The Alias Method

11.5　Stochastic Processes

11.5.1　Simulating a Nonhomogeneous Poisson Process

11.5.2　Simulating a Two-Dimensional Poisson Process

11.8.1　Coupling from the Pas

11.8.2　Another Approach

Exercises

References

Appendix: Solutions to Starred Exercises

Index

作者介紹

Sheldon M. Ross 國際知名概率與統(tǒng)計學家，南加州大學工業(yè)工程與運籌系系主任。1968年博士畢業(yè)于斯坦福大學統(tǒng)計系，曾在加州大學伯克利分校任教多年。研究領(lǐng)域包括：隨機模型、仿真模擬、統(tǒng)計分析、金融數(shù)學等。Ross教授著述頗豐，，他的多種暢銷數(shù)學和統(tǒng)計教材均產(chǎn)生了世界性的影響，如《概率論基礎(chǔ)教程（第8版）》等。

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應(yīng)用隨機過程：概率模型導論（第11版）