| Edition |
9th ed. |
| Description |
1 online resource (xviii, 782 pages) : illustrations |
| Physical Medium |
polychrome |
| Description |
text file |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Cover -- Title page -- Copyright page -- Contents -- Preface -- Chapter 1. Introduction to Probability Theory -- 1.1. Introduction -- 1.2. Sample Space and Events -- 1.3. Probabilities Defined on Events -- 1.4. Conditional Probabilities -- 1.5. Independent Events -- 1.6. Bayes' Formula -- Exercises -- References -- Chapter 2. Random Variables -- 2.1. Random Variables -- 2.2. Discrete Random Variables -- 2.3. Continuous Random Variables -- 2.4. Expectation of a Random Variable -- 2.5. Jointly Distributed Random Variables -- 2.6. Moment Generating Functions -- 2.7. Limit Theorems -- 2.8. Stochastic Processes -- Exercises -- References -- Chapter 3. Conditional Probability and Conditional Expectation -- 3.1. Introduction -- 3.2. The Discrete Case -- 3.3. The Continuous Case -- 3.4. Computing Expectations by Conditioning -- 3.5. Computing Probabilities by Conditioning -- 3.6. Some Applications -- 3.7. An Identity for Compound Random Variables -- Exercises -- Chapter 4. Markov Chains -- 4.1. Introduction -- 4.2. Chapman-Kolmogorov Equations -- 4.3. Classification of States -- 4.4. Limiting Probabilities -- 4.5. Some Applications -- 4.6. Mean Time Spent in Transient States -- 4.7. Branching Processes -- 4.8. Time Reversible Markov Chains -- 4.9. Markov Chain Monte Carlo Methods -- 4.10. Markov Decision Processes -- 4.11. Hidden Markov Chains -- Exercises -- References -- Chapter 5. The Exponential Distribution and the Poisson Process -- 5.1. Introduction -- 5.2. The Exponential Distribution -- 5.3. The Poisson Process -- 5.4. Generalizations of the Poisson Process -- Exercises -- References -- Chapter 6. Continuous-Time Markov Chains -- 6.1. Introduction -- 6.2. Continuous-Time Markov Chains -- 6.3. Birth and Death Processes -- 6.4. The Transition Probability Function Pij(t) -- 6.5. Limiting Probabilities -- 6.6. Time Reversibility -- 6.7. Uniformization -- 6.8. Computing the Transition Probabilities -- Exercises -- References -- Chapter 7. Renewal Theory and Its Applications -- 7.1. Introduction -- 7.2. Distribution of N(t) -- 7.3. Limit Theorems and Their Applications -- 7.4. Renewal Reward Processes -- 7.5. Regenerative Processes -- 7.6. Semi-Markov Processes -- 7.7. The Inspection Paradox -- 7.8. Computing the Renewal Function -- 7.9. Applications to Patterns -- 7.10. The Insurance Ruin Problem -- Exercises -- References -- Chapter 8. Queueing Theory -- 8.1. Introduction -- 8.2. Preliminaries -- 8.3. Exponential Models -- 8.4. Network of Queues -- 8.5. The System M/G/1 -- 8.6. Variations on the M/G/1 -- 8.7. The Model G/M/1 -- 8.8. A Finite Source Model -- 8.9. Multiserver Queues -- Exercises -- References -- Chapter 9. Reliability Theory -- 9.1. Introduction -- 9.2. Structur. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Subject |
Probabilities.
|
|
Probabilities. |
| Genre/Form |
Electronic books.
|
| Other Form: |
Print version: Ross, Sheldon M. Introduction to probability models. 9th ed. Amsterdam ; Boston : Academic Press, ©2007 9780125980623 0125980620 (DLC) 2006051040 (OCoLC)71552484 |
| ISBN |
9780080467825 (electronic book) |
|
0080467822 (electronic book) |
|
9780125980623 (acid-free paper) |
|
0125980620 (acid-free paper) |
|
9780123736352 (paperback ; acid-free paper) |
|
0123736358 (paperback ; acid-free paper) |
|
