Introduction Stochastic Processes by Peterson Jonathon (18 results)

Condition: New.

Paperback. Condition: New. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes.…

Paperback. Condition: Brand New. 324 pages. 6.00x0.73x9.00 inches. In Stock.

Condition: New.

Paperback. Condition: New. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes.…

Hardback. Condition: New. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes.…

Hardcover. Condition: Brand New. 324 pages. 6.24x0.95x9.24 inches. In Stock.

Hardback. Condition: New. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes.…

Paperback. Condition: new. Paperback. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condition: new. Hardcover. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes.…

Taschenbuch. Condition: Neu. INTRODUCTION TO STOCHASTIC PROCESSES, AN | Peterson Jonathon | Taschenbuch | SUSTAINABLE CHEMISTRY SERIES | Englisch | 2026 | World Scientific | EAN 9789819833832 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Hardcover. Condition: new. Hardcover. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condition: new. Hardcover. An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Condition: Neu. An Introduction to Stochastic Processes | Peterson Jonathon | Buch | Englisch | 2026 | World Scientific | EAN 9789819833771 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An Introduction to Stochastic Processes provides a clear and rigorous introduction to the theory and applications of stochastic processes. The book begins with an introductory chapter that reviews essential probability tools, including computing by conditioning and the law of large numbers, while introducing classical processes such as random walks, gambler's ruin, and branching processes. Key concepts like renewal processes and stopping times are also presented, providing a foundation for the rest of the text.Markov chains and continuous-time Markov processes are treated on both finite and countable state spaces, with elementary proofs of central results such as limiting distributions and ergodic theorems. Differences between finite and countable settings are highlighted to enhance understanding, and martingales are introduced as a powerful framework for analyzing stochastic processes. The presentation remains accessible to students with a background in basic probability and linear algebra, without requiring measure theory.Poisson processes are developed beyond the traditional one-dimensional case to include multi-dimensional processes, expanding applications while maintaining clarity. The book also provides a simple algorithm for generating non-homogeneous Poisson processes in any dimension. Packed with examples and exercises of varying difficulty, this text bridges theory and practice, making it an essential resource for students, instructors, and anyone seeking a solid foundation in stochastic processes.…