Characterizations of Recently Introduced Univariate Continuous Distributions II
Book Details
Format
Hardback or Cased Book
ISBN-10
1536150959
ISBN-13
9781536150957
Publisher
Nova Science Publishers Inc
Imprint
Nova Science Publishers Inc
Country of Manufacture
US
Country of Publication
GB
Publication Date
May 17th, 2019
Print length
436 Pages
Weight
942 grams
Dimensions
18.70 x 26.00 x 2.50 cms
Product Classification:
Probability & statisticsProbability and statistics
Ksh 36,700.00
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This monograph is, as far as the author has gathered, the second of its kind (the first one was published by Nova in 2017 with coauthors Hamedani and Maadooliat) which presents various characterizations of a wide variety of continuous distributions. These two monographs could also be used as sources to prevent reinventing and duplicating the already exiting distributions. The current book consists of seven chapters. The first chapter lists cumulative and density functions of two hundred and twenty univariate distributions. Chapter two provides characterizations of these distributions: (i) based on the ration of two truncated moments; (ii) in terms of the hazard function; (iii) in terms of the reverse hazard function; (iv) based on the conditional expectation of certain functions of the random variable. Chapter three includes the characterizations of twenty distributions, which appeared in a published paper (Hamedani and Safavimanesh, 2017). Chapter four presents characterizations of thirty six distributions, contains a published paper (Hamedani, 2017). Chapter five covers the characterizations of forty one distributions, which appeared in a published paper (Hamedani, 2018a). Chapter six presents characterizations of eighty distributions, contained in a published paper (Hamedani, 2018b). Finally, chapter seven consists of seventy proposed distributions. The main reason to include previously published papers in Chapters 3-6 is to provide a rather complete source for the interested researchers who would want to avoid reinventing the existing distributions.
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