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Stochastic Comparisons With Applications In Order Statistics And Spacings Subhash C Kochar

  • SKU: BELL-46771140
Stochastic Comparisons With Applications In Order Statistics And Spacings Subhash C Kochar
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Stochastic Comparisons With Applications In Order Statistics And Spacings Subhash C Kochar instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 3.62 MB
Pages: 280
Author: Subhash C. Kochar
ISBN: 9783031121036, 3031121031
Language: English
Year: 2022

Product desciption

Stochastic Comparisons With Applications In Order Statistics And Spacings Subhash C Kochar by Subhash C. Kochar 9783031121036, 3031121031 instant download after payment.

This book emphasizes the use of stochastic orders as motivational tools for developing new statistical procedures. Stochastic orders have found useful applications in many disciplines, including reliability theory, survival analysis, risk theory, finance, nonparametric methods, economics and actuarial science. Written by a statistician, this volume clarifies the connection between stochastic orders and nonparametric methods. The importance of order statistics and spacings is well recognized. Classically, they mainly focus on the case when the observations are independent and identically distributed, however, several new developments have extended the comparison of order statistics to the case of non-identically distributed or non-independent observations. In addition to giving a detailed discussion of various topics in the general area of stochastic orders, a substantial part of the book is devoted to recent research on stochastic comparisons of order statistics and spacings, including a long chapter on dependence among them. The book will be useful for graduate students and researchers in statistics, economics, actuarial science and other related disciplines. In particular, with close to 300 references, it will be a valuable resource for reliability theorists, applied probabilists and statisticians. Readers are expected to have taken a first-year graduate level course in mathematical statistics or in applied probability.

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