Matrix-analytic methods in stochastic models

Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models.  Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrin...

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書誌詳細
第一著者: Latouche, Guy
その他の著者: Ramaswami, Vaidyanathan (出版デイレクター), Sethuraman, Jay (出版デイレクター), Sigman, Karl (出版デイレクター), Squillante, Mark S. (出版デイレクター), Yao, David (出版デイレクター)
フォーマット: Livre numérique
言語:Anglais
出版事項: New York, NY : Springer New York [20..].
Cham : Springer Nature
版:1st ed. 2013.
シリーズ:Springer Proceedings in Mathematics & Statistics 27
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注記: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Matrix-Analytic Methods in Stochastic Models, Texte imprimé, 9781461449089
• Matrix-Analytic Methods in Stochastic Models, Texte imprimé, 9781461449102
• Matrix-Analytic Methods in Stochastic Models, Texte imprimé, 9781489994240
その他の書誌記述
要約:Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models.  Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., performance measures) of the underlying stochastic processes, and apply these probabilistic structures and/or computational algorithms within a wide variety of fields.  This volume presents recent research results on: the theory, algorithms and methodologies concerning matrix-analytic and related methods in stochastic models; and the application of matrix-analytic and related methods in various fields, which includes but is not limited to computer science and engineering, communication networks and telephony, electrical and industrial engineering, operations research, management science, financial and risk analysis, and bio-statistics.  These research studies provide deep insights and understanding of the stochastic models of interest from a mathematics and applications perspective, as well as identify directions for future research
記述事項:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9781461449096
ISSN:2194-1017
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