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Titlebook: Elementary Probability Theory with Stochastic Processes; Kai Lai Chung Textbook 19793rd edition Springer-Verlag New York 1979 Probability.

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书目名称Elementary Probability Theory with Stochastic Processes
编辑Kai Lai Chung
视频video
丛书名称Undergraduate Texts in Mathematics
图书封面Titlebook: Elementary Probability Theory with Stochastic Processes;  Kai Lai Chung Textbook 19793rd edition Springer-Verlag New York 1979 Probability.
描述A new feature of this edition consists of photogra phs of eight masters in the contemporary development of probability theory. All of them appear in the body of the book, though the few references there merely serve to give a glimpse of their manifold contributions. It is hoped that these vivid pictures will inspire in the reader a feeling that our science is a live endeavor created and pursued by real personalities. I have had the privilege of meeting and knowing most of them after studying their works and now take pleasure in introducing them to a younger generation. In collecting the photographs I had the kind assistance of Drs Marie-Helene Schwartz, Joanne Elliot, Milo Keynes and Yu. A. Rozanov, to whom warm thanks are due. A German edition of the book has just been published. I am most grateful to Dr. Herbert Vogt for his careful translation which resulted also in a consid­ erable number of improvements on the text of this edition. Other readers who were kind enough to send their comments include Marvin Greenberg, Louise Hay, Nora Holmquist, H. -E. Lahmann, and Fred Wolock. Springer-Verlag is to be complimented once again for its willingness to make its books "immer besser. "
出版日期Textbook 19793rd edition
关键词Probability; Probability theory; Stochastic processes; Stochastischer Prozess; Wahrscheinlichkeitsrechnu
版次3
doihttps://doi.org/10.1007/978-1-4684-9346-7
isbn_ebook978-1-4684-9346-7Series ISSN 0172-6056 Series E-ISSN 2197-5604
issn_series 0172-6056
copyrightSpringer-Verlag New York 1979
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Mean, Variance and Transforms,an)” or “its expectation exists.” The last expression is actually a little vague because we generally allow .(.) to be defined and equal to +∞ when for instance . 0 and the series in (6.1.1) diverges. See Exercises 27 and 28 of Chapter 4. We shall say so explicitly when this is the case.
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From Random Walks to Markov Chains,is. This set is often referred to as the “integer lattice” on .. = (-∞, ∞) and will be denoted by .. Thus the particle executes a walk on the lattice, back and forth, and continues . If we plot its position .. as a function of the time ., its . is a zigzag line of which some samples are shown below in Figure 30.
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Counting,tions arising from sampling, ranking, partitioning, allocating, programming and model building, to mention a few. In this chapter we shall treat the most elementary and basic types of problems and the methods of solving them.
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