An Introduction to Stochastic Orders

Nonfiction, Science & Nature, Mathematics, Probability, Statistics
Cover of the book An Introduction to Stochastic Orders by Felix Belzunce, Carolina Martinez Riquelme, Julio Mulero, Elsevier Science
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Author: Felix Belzunce, Carolina Martinez Riquelme, Julio Mulero ISBN: 9780128038260
Publisher: Elsevier Science Publication: September 29, 2015
Imprint: Academic Press Language: English
Author: Felix Belzunce, Carolina Martinez Riquelme, Julio Mulero
ISBN: 9780128038260
Publisher: Elsevier Science
Publication: September 29, 2015
Imprint: Academic Press
Language: English

An Introduction to Stochastic Orders discusses this powerful tool that can be used in comparing probabilistic models in different areas such as reliability, survival analysis, risks, finance, and economics. The book provides a general background on this topic for students and researchers who want to use it as a tool for their research.

In addition, users will find detailed proofs of the main results and applications to several probabilistic models of interest in several fields, and discussions of fundamental properties of several stochastic orders, in the univariate and multivariate cases, along with applications to probabilistic models.

  • Introduces stochastic orders and its notation
  • Discusses different orders of univariate stochastic orders
  • Explains multivariate stochastic orders and their convex, likelihood ratio, and dispersive orders
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An Introduction to Stochastic Orders discusses this powerful tool that can be used in comparing probabilistic models in different areas such as reliability, survival analysis, risks, finance, and economics. The book provides a general background on this topic for students and researchers who want to use it as a tool for their research.

In addition, users will find detailed proofs of the main results and applications to several probabilistic models of interest in several fields, and discussions of fundamental properties of several stochastic orders, in the univariate and multivariate cases, along with applications to probabilistic models.

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