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Stochastic processes and applications in biology and medicine I: Theory: Biomathematics, cartea 3

Autor Marius Iosifescu, P. Tautu
en Limba Engleză Paperback – 28 ian 2012
This volume is a revised and enlarged version of Chapters 1 and 2 of a book with the same title, published in Romanian in 1968. The revision resulted in a new book which has been divided into two parts because of the large amount of new material. The present part is intended to introduce mathematicians and biologists with a strong mathematical and probabilistic background to the study of stochastic processes. We hope some readers will be able to discover by themselves the new features of our treatment such as the inclusion of some unusual topics, the special attention paid to some usual topics, and the grouping of the material. We draw the reader's attention to the numbering, because there are structural differences between the two parts. In Part I there are Chapters, Sections, Subsections, Paragraphs and Subparagraphs. Thus the numbering a. b. c. d. e refers to Subparagraph e of Paragraph d of Subsection c of Section b of Chapter a. Definitions, theorems lemmas and propositions are numbered a. b. n, n = 1,2, . . . , where a indicates the chapter and b the section. In Part II there are Sections, Subsections, Paragraphs, and SUbparagraphs. Thus the numbering a. b. c. d refers to Subparagraph d of Paragraph c of Subsection b of Section a. Theorems and lemmas are numbered a. n, n = 1, 2, . . . , where a indicates the section.
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Specificații

ISBN-13: 9783642807527
ISBN-10: 3642807526
Pagini: 332
Ilustrații: 332 p.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.47 kg
Ediția:Softcover reprint of the original 1st ed. 1973
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Biomathematics

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

1 Discrete parameter stochastic processes.- 1.1. Denumerable Markov chains.- 1.2. Noteworthy classes of denumerable Markov chains.- 1.3. Markov chains with arbitrary state space.- References.- 2 Continuous parameter stochastic processes.- 2.1. Some general problems.- 2.2. Processes with independent increments.- 2.3. Markov processes.- References.- Notation index.- Author index.