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Titlebook: Life Distributions; Structure of Nonpara Albert W. Marshall,Ingram Olkin Book 2007 Springer-Verlag New York 2007 Descriptive statistics.Gau

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书目名称Life Distributions
副标题Structure of Nonpara
编辑Albert W. Marshall,Ingram Olkin
视频video
概述Devoted to the study of univariate distributions appropriate for the analyses of data known to be nonnegative.Includes much material from reliability theory in engineering and survival analysis in med
丛书名称Springer Series in Statistics
图书封面Titlebook: Life Distributions; Structure of Nonpara Albert W. Marshall,Ingram Olkin Book 2007 Springer-Verlag New York 2007 Descriptive statistics.Gau
描述.For over 200 years, practitioners have been developing parametric families of probability distributions for data analysis. More recently, an active development of nonparametric and semiparametric families has occurred. This book includes an extensive discussion of a wide variety of distribution families—nonparametric, semiparametric and parametric—some well known and some not. An all-encompassing view is taken for the purpose of identifying relationships, origins and structures of the various families. A unified methodological approach for the introduction of parameters into families is developed, and the properties that the parameters imbue a distribution are clarified. These results provide essential tools for intelligent choice of models for data analysis. Many of the results given are new and have not previously appeared in print. This book provides a comprehensive reference for anyone working with nonnegative data..
出版日期Book 2007
关键词Descriptive statistics; Gaussian distribution; Normal distribution; Probability distribution; Probabilit
版次1
doihttps://doi.org/10.1007/978-0-387-68477-2
isbn_softcover978-1-4419-1911-3
isbn_ebook978-0-387-68477-2Series ISSN 0172-7397 Series E-ISSN 2197-568X
issn_series 0172-7397
copyrightSpringer-Verlag New York 2007
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Ordering Distributions: Descriptive Statisticss were often defined as “that which the measure measures.” The standard deviation as a measure of dispersion or spread is a familiar example, but measures of skewness and kurtosis based on moments were also proposed by Pearson (1895).
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Nonparametric Families: Densities and Hazard Ratestion that a distribution lies in a particular family sometimes can be justified by a physical understanding of the failure mechanism. For these nonparametric families, many statistical procedures are available that can be regarded as standing between parametric and standard distribution-free analyses.
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Gompertz and Gompertz-Makeham Distributions to gain wide attention was that of Gompertz (1825). This family was extended with the addition of a parameter by Makeham (1860), and subsequently by various other authors. An historical review of considerable interest has been given by Ogborn (1953).
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Book 2007oped, and the properties that the parameters imbue a distribution are clarified. These results provide essential tools for intelligent choice of models for data analysis. Many of the results given are new and have not previously appeared in print. This book provides a comprehensive reference for anyone working with nonnegative data..
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0172-7397 liability theory in engineering and survival analysis in med.For over 200 years, practitioners have been developing parametric families of probability distributions for data analysis. More recently, an active development of nonparametric and semiparametric families has occurred. This book includes a
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Book 2007evelopment of nonparametric and semiparametric families has occurred. This book includes an extensive discussion of a wide variety of distribution families—nonparametric, semiparametric and parametric—some well known and some not. An all-encompassing view is taken for the purpose of identifying rela
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