[PDF.24qz] Decoupling: From Dependence to Independence (Probability and Its Applications)

Decoupling: From Dependence to Independence (Probability and Its Applications)

[PDF.ax77] Decoupling: From Dependence to Independence (Probability and Its Applications)

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 |  Evarist Gin Victor de la Pea |  1998-12-21 |  1998-12-21 | Original language:English | PDF # 1 |  9.25 x.93 x6.10l,1.27 | File type: PDF | 392 pages

 | Decoupling From Dependence to Independence Probability and Its Applications

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||3 of 3 people found the following review helpful.| technique for using independence properties for dependent data|By Michael R. Chernick|This is a highly theoretical text that covers a topic that many statisticians and even some probabilist are not familiar with. Modeling dependent data is more complicated and complex compared to independent data. Decoupling is a general approach that uses probability inequalities to relate j| ||From a review: |MATHEMATICAL REVIEWS |"The book is written in an excellent way. The exposition is clear and effective. The results are well motivated."

A friendly and systematic introduction to the theory and applications. The book begins with the sums of independent random variables and vectors, with maximal inequalities and sharp estimates on moments, which are later used to develop and interpret decoupling inequalities. Decoupling is first introduced as it applies to randomly stopped processes and unbiased estimation. The authors then proceed with the theory of decoupling in full generality, paying special attention ...

You easily download any file type for your device.Decoupling: From Dependence to Independence (Probability and Its Applications)   |  Victor de la Peña, Evarist Giné. A good, fresh read, highly recommended.

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