Titlebook: Stochastic Orders; Moshe Shaked,J. George Shanthikumar Book 2007 Springer-Verlag New York 2007 Convexity.Monotone.decision making.form.man

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The Laplace Transform and Related Orders,Laplace transform order compares random variables according to both their “location” and their “spread”. Two other useful orders, based on ratios of Laplace transforms, are also discussed in this chapter. In addition, some other related orders are investigated in this chapter as well.

CHANT

Multivariate Variability and Related Orders, common orders that are studied in this chapter are the increasing and the directional convex and concave orders. Multivariate extensions of the order ≤. are also studied in this chapter. Some multivariate extensions of the transform orders, and of the Laplace transform order, are investigated in this chapter as well.

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Moshe Shaked,J. George ShanthikumarA major extension of the first six chapters in Shaked and Shanthikumar‘s 1994 book.Since 1994, the theory of stochastic orders has grown significantly

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Springer Series in Statisticshttp://image.papertrans.cn/s/image/878069.jpg

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https://doi.org/10.1007/978-0-387-34675-5Convexity; Monotone; decision making; form; management; operations research; statistics; stochastic systems

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ilable on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) 978-3-030-00337-1978-3-030-00338-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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0172-7397 complex stochastic systems. It is suitable as a text for advanced graduate course on stochastic ordering and applications..978-1-4419-2195-6978-0-387-34675-5Series ISSN 0172-7397 Series E-ISSN 2197-568X

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egation) to naturally capture data analytics tasks, but at the same time carefully restricts the interaction of recursion and arithmetic to preserve decidability of reasoning. We concentrate on the positive language, but also discuss several generalisations and fragments of positive Limit Datalog, w