An edition of Applications of semi-regenerative theory to computations of stationary distributions of Markov chains (1982)

Applications of semi-regenerative theory to computations of stationary distributions of Markov chains

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Applications of semi-regenerative theory to c ...
Winfried K. Grassmann, Winfrie ...
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Last edited by WorkBot
December 15, 2009 | History
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An edition of Applications of semi-regenerative theory to computations of stationary distributions of Markov chains (1982)

Applications of semi-regenerative theory to computations of stationary distributions of Markov chains

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Publish Date
Publisher
Institute for Mathematical Studies in the Social Sciences, Stanford University
Language
English
Pages
21

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Subjects

Queuing theory, Birth and death processes (Stochastic processes), Markov processes

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Edition Availability
Cover of: Applications of semi-regenerative theory to computations of stationary distributions of Markov chains
Applications of semi-regenerative theory to computations of stationary distributions of Markov chains
1982, Institute for Mathematical Studies in the Social Sciences, Stanford University
in English
  • Not in Library

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Book Details

Edition Notes

"A report of the Center for Research on Organizational Efficiency, Stanford University, contract ONR-N00014-79-C-0685, United States Office of Naval Research and the National Science Foundation grants ECS 8204540 and ECS 8017867."

Bibliography: p. 21.

Published in
Stanford, Calif
Series
Technical report / Institute for Mathematical Studies in the Social Sciences -- no. 403, Economics series / Institute for Mathematical Studies in the Social Sciences, Technical report (Stanford University. Institute for Mathematical Studies in the Social Sciences) -- no. 403., Economics series (Stanford University. Institute for Mathematical Studies in the Social Sciences)

The Physical Object

Pagination
21 p. ;
Number of pages
21

ID Numbers

Open Library
OL22408994M

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December 15, 2009 Edited by WorkBot link works
November 12, 2008 Created by ImportBot Imported from Binghamton University MARC record