Ebook: Applied Stochastic Processes

Applied Stochastic Processes uses a distinctly applied framework to present the most important topics in the field of stochastic processes.

Key features:

-Presents carefully chosen topics such as Gaussian and Markovian processes, Markov chains, Poisson processes, Brownian motion, and queueing theory

-Examines in detail special diffusion processes, with implications for finance, various generalizations of Poisson processes, and renewal processes

-Serves graduate students in a variety of disciplines such as applied mathematics, operations research, engineering, finance, and business administration

-Contains numerous examples and approximately 350 advanced problems, reinforcing both concepts and applications

-Includes entertaining mini-biographies of mathematicians, giving an enriching historical context

-Covers basic results in probability

Two appendices with statistical tables and solutions to the even-numbered problems are included at the end. This textbook is for graduate students in applied mathematics, operations research, and engineering. Pure mathematics students interested in the applications of probability and stochastic processes and students in business administration will also find this book useful.

Bio: Mario Lefebvre received his B.Sc. and M.Sc. in mathematics from the Université de Montréal, Canada, and his Ph.D. in mathematics from the University of Cambridge, England. He is a professor in the Department of Mathematics and Industrial Engineering at the École Polytechnique de Montréal. He has written five books, including another Springer title, Applied Probability and Statistics, and has published numerous papers on applied probability, statistics, and stochastic processes in international mathematical and engineering journals. This book developed from the author’s lecture notes for a course he has taught at the École Polytechnique de Montréal since 1988.

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Applied Stochastic Processes uses a distinctly applied framework to present the most important topics in the field of stochastic processes.

Key features:

-Presents carefully chosen topics such as Gaussian and Markovian processes, Markov chains, Poisson processes, Brownian motion, and queueing theory

-Examines in detail special diffusion processes, with implications for finance, various generalizations of Poisson processes, and renewal processes

-Serves graduate students in a variety of disciplines such as applied mathematics, operations research, engineering, finance, and business administration

-Contains numerous examples and approximately 350 advanced problems, reinforcing both concepts and applications

-Includes entertaining mini-biographies of mathematicians, giving an enriching historical context

-Covers basic results in probability

Two appendices with statistical tables and solutions to the even-numbered problems are included at the end. This textbook is for graduate students in applied mathematics, operations research, and engineering. Pure mathematics students interested in the applications of probability and stochastic processes and students in business administration will also find this book useful.

Bio: Mario Lefebvre received his B.Sc. and M.Sc. in mathematics from the Universit? de Montr?al, Canada, and his Ph.D. in mathematics from the University of Cambridge, England. He is a professor in the Department of Mathematics and Industrial Engineering at the ?cole Polytechnique de Montr?al. He has written five books, including another Springer title, Applied Probability and Statistics, and has published numerous papers on applied probability, statistics, and stochastic processes in international mathematical and engineering journals. This book developed from the author’s lecture notes for a course he has taught at the ?cole Polytechnique de Montr?al since 1988.

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Applied Stochastic Processes uses a distinctly applied framework to present the most important topics in the field of stochastic processes.

Key features:

-Presents carefully chosen topics such as Gaussian and Markovian processes, Markov chains, Poisson processes, Brownian motion, and queueing theory

-Examines in detail special diffusion processes, with implications for finance, various generalizations of Poisson processes, and renewal processes

-Serves graduate students in a variety of disciplines such as applied mathematics, operations research, engineering, finance, and business administration

-Contains numerous examples and approximately 350 advanced problems, reinforcing both concepts and applications

-Includes entertaining mini-biographies of mathematicians, giving an enriching historical context

-Covers basic results in probability

Two appendices with statistical tables and solutions to the even-numbered problems are included at the end. This textbook is for graduate students in applied mathematics, operations research, and engineering. Pure mathematics students interested in the applications of probability and stochastic processes and students in business administration will also find this book useful.

Bio: Mario Lefebvre received his B.Sc. and M.Sc. in mathematics from the Universit? de Montr?al, Canada, and his Ph.D. in mathematics from the University of Cambridge, England. He is a professor in the Department of Mathematics and Industrial Engineering at the ?cole Polytechnique de Montr?al. He has written five books, including another Springer title, Applied Probability and Statistics, and has published numerous papers on applied probability, statistics, and stochastic processes in international mathematical and engineering journals. This book developed from the author’s lecture notes for a course he has taught at the ?cole Polytechnique de Montr?al since 1988.

Content:
Front Matter....Pages i-xiii
Review of Probability Theory....Pages 1-45
Stochastic Processes....Pages 47-72
Markov Chains....Pages 73-172
Diffusion Processes....Pages 173-229
Poisson Processes....Pages 231-313
Queueing Theory....Pages 315-356
Back Matter....Pages 357-386

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Applied Stochastic Processes uses a distinctly applied framework to present the most important topics in the field of stochastic processes.

Key features:

-Presents carefully chosen topics such as Gaussian and Markovian processes, Markov chains, Poisson processes, Brownian motion, and queueing theory

-Examines in detail special diffusion processes, with implications for finance, various generalizations of Poisson processes, and renewal processes

-Serves graduate students in a variety of disciplines such as applied mathematics, operations research, engineering, finance, and business administration

-Contains numerous examples and approximately 350 advanced problems, reinforcing both concepts and applications

-Includes entertaining mini-biographies of mathematicians, giving an enriching historical context

-Covers basic results in probability

Two appendices with statistical tables and solutions to the even-numbered problems are included at the end. This textbook is for graduate students in applied mathematics, operations research, and engineering. Pure mathematics students interested in the applications of probability and stochastic processes and students in business administration will also find this book useful.

Bio: Mario Lefebvre received his B.Sc. and M.Sc. in mathematics from the Universit? de Montr?al, Canada, and his Ph.D. in mathematics from the University of Cambridge, England. He is a professor in the Department of Mathematics and Industrial Engineering at the ?cole Polytechnique de Montr?al. He has written five books, including another Springer title, Applied Probability and Statistics, and has published numerous papers on applied probability, statistics, and stochastic processes in international mathematical and engineering journals. This book developed from the author’s lecture notes for a course he has taught at the ?cole Polytechnique de Montr?al since 1988.

Content:
Front Matter....Pages i-xiii
Review of Probability Theory....Pages 1-45
Stochastic Processes....Pages 47-72
Markov Chains....Pages 73-172
Diffusion Processes....Pages 173-229
Poisson Processes....Pages 231-313
Queueing Theory....Pages 315-356
Back Matter....Pages 357-386
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