Introduction to probability and stochastic processes with applications

Introduction to probability and stochastic processes with applications /

"This text book is designed for a one-year course in probability and stochastic processes with applications, especially for students who wish to specialize in probabilistic modeling. This book bridges the gap between elementary texts and advanced texts in probability and is easily accessible fo...

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Bibliographic Details
Online Access: Full text (MCPHS users only)
Main Author: Blanco Castañeda, Liliana
Other Authors: Arunachalam, Viswanathan, 1969-, Dharmaraja, Selvamuthu, 1972-
Format: Electronic eBook
Language:English
Published: Hoboken, NJ : Wiley, 2012
Subjects:
Probabilities > Textbooks.
Stochastic processes > Textbooks.
Local Note:ProQuest Ebook Central

MARC

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100 1 |a Blanco Castañeda, Liliana. 
245 1 0 |a Introduction to probability and stochastic processes with applications /  |c Liliana Blanco Castaneda, Viswanathan Arunachalam, Selvamuthu Dharmaraja. 
260 |a Hoboken, NJ :  |b Wiley,  |c 2012. 
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504 |a Includes bibliographical references and index. 
505 0 |a Front Matter -- Basic Concepts -- Random Variables and Their Distributions -- Some Discrete Distributions -- Some Continuous Distributions -- Random Vectors -- Conditional Expectation -- Multivariate Normal Distributions -- Limit Theorems -- Introduction to Stochastic Processes -- Introduction to Queueing Models -- Stochastic Calculus -- Introduction to Mathematical Finance -- Appendix A: Basic Concepts on Set Theory -- Appendix B: Introduction to Combinatorics -- Appendix C: Topics on Linear Algebra -- Appendix D: Statistical Tables -- Selected Problem Solutions -- References -- Glossary -- Index. 
520 |a "This text book is designed for a one-year course in probability and stochastic processes with applications, especially for students who wish to specialize in probabilistic modeling. This book bridges the gap between elementary texts and advanced texts in probability and is easily accessible for students with diverse backgrounds and majoring in engineering, applied sciences, business and finance, statistics, mathematics, and operations research. The text contains many examples and exercises which have been tested in classrooms and are chosen from diverse areas such as queuing models, reliability and finance. Chapter coverage includes: basic concepts; random variables and their distributions; discrete distributions; continuous distributions; random vectors; multivariate normal distributions; conditional expectation; limit theorems; stochastic processes; queuing models; stochastic calculus; and mathematical finance"--  |c Provided by publisher. 
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700 1 |a Dharmaraja, Selvamuthu,  |d 1972-  |1 https://id.oclc.org/worldcat/entity/E39PCjBQgKjy8YVRcRKgKH63Qq 
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880 0 |6 505-00/(S  |a Introduction to Probability and Stochastic Processes with Applications -- CONTENTS -- Foreword -- Preface -- Acknowledgments -- Introduction -- 1 Basic Concepts -- 1.1 Probability Space -- 1.2 Laplace Probability Space -- 1.3 Conditional Probability and Event Independence -- 1.4 Geometric Probability -- Exercises -- 2 Random Variables and Their Distributions -- 2.1 Definitions and Properties -- 2.2 Discrete Random Variables -- 2.3 Continuous Random Variables -- 2.4 Distribution of a Function of a Random Variable -- 2.5 Expected Value and Variance of a Random Variable -- Exercises -- 3 Some Discrete Distributions -- 3.1 Discrete Uniform, Binomial and Bernoulli Distributions -- 3.2 Hypergeometric and Poisson Distributions -- 3.3 Geometric and Negative Binomial Distributions -- Exercises -- 4 Some Continuous Distributions -- 4.1 Uniform Distribution -- 4.2 Normal Distribution -- 4.3 Family of Gamma Distributions -- 4.4 Weibull Distribution -- 4.5 Beta Distribution -- 4.6 Other Continuous Distributions -- Exercises -- 5 Random Vectors -- 5.1 Joint Distribution of Random Variables -- 5.2 Independent Random Variables -- 5.3 Distribution of Functions of a Random Vector -- 5.4 Covariance and Correlation Coefficient -- 5.5 Expected Value of a Random Vector and Variance-Covariance Matrix -- 5.6 Joint Probability Generating, Moment Generating and Characteristic Functions -- Exercises -- 6 Conditional Expectation -- 6.1 Conditional Distribution -- 6.2 Conditional Expectation Given a σ-Algebra -- Exercises -- 7 Multivariate Normal Distributions -- 7.1 Multivariate Normal Distribution -- 7.2 Distribution of Quadratic Forms of Multivariate Normal Vectors -- Exercises -- 8 Limit Theorems -- 8.1 The Weak Law of Large Numbers -- 8.2 Convergence of Sequences of Random Variables -- 8.3 The Strong Law of Large Numbers -- 8.4 Central Limit Theorem -- Exercises. 
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