Applied Probability Models with Optimization Applications (Dover Books on Mathematics). Cet article n’est pas disponible.
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Langue : anglais
Edité par Dover Pubns, 1992
- Livre broché
- Neuf

Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
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Vendeur AbeBooks depuis 6 janvier 2003
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Livre broché
Etat: Neuf
EUR 25,84
Item description from seller
reprint edition. 198 pages. 8.75x5.50x0.50 inches. In Stock.
N° de réf. du vendeur 0486673146
- Titre
- Applied Probability Models with Optimization Applications (Dover Books on Mathematics)
- Auteur
- Sheldon M. Ross
- Éditeur
- Dover Pubns
- Année de publication
- 1992
- État de l'article
- Brand New
- Reliure
- Paperback
- Langue
- anglais
- ISBN à 10 chiffres
- 0486673146
- ISBN à 13 chiffres
- 9780486673141
- Poids de l'article
- 0,23 kilogramme
"A clarity of style and a conciseness of treatment which students will find most welcome. The material is valuable and well organized ... an excellent introduction to applied probability." -- Journal of the American Statistical Association.
This book offers a concise introduction to some of the stochastic processes that frequently arise in applied probability. Emphasis is on optimization models and methods, particularly in the area of decision processes. After reviewing some basic notions of probability theory and stochastic processes, the author presents a useful treatment of the Poisson process, including compound and nonhomogeneous Poisson processes. Subsequent chapters deal with such topics as renewal theory and Markov chains; semi-Markov, Markov renewal, and regenerative processes; inventory theory; and Brownian motion and continuous time optimization models.
Each chapter is followed by a section of useful problems that illustrate and complement the text. There is also a short list of relevant references at the end of every chapter. Students will find this a largely self-contained text that requires little previous knowledge of the subject. It is especially suited for a one-year course in applied probability at the advanced undergraduate or beginning postgraduate level. 1970 edition.
This book offers a concise introduction to some of the stochastic processes that frequently arise in applied probability. Emphasis is on optimization models and methods, particularly in the area of decision processes. After reviewing some basic notions of probability theory and stochastic processes, the author presents a useful treatment of the Poisson process, including compound and nonhomogeneous Poisson processes. Subsequent chapters deal with such topics as renewal theory and Markov chains; semi-Markov, Markov renewal, and regenerative processes; inventory theory; and Brownian motion and continuous time optimization models.
Each chapter is followed by a section of useful problems that illustrate and complement the text. There is also a short list of relevant references at the end of every chapter. Students will find this a largely self-contained text that requires little previous knowledge of the subject. It is especially suited for a one-year course in applied probability at the advanced undergraduate or beginning postgraduate level. 1970 edition.
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