文章基本信息

标题：Estimation of Parameters of Johnson’s System of Distributions
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作者：George, Florence ; Ramachandran, K. M.
期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2011
卷号：10
期号：2
页码：9
出版社：Wayne State University
摘要：Fitting distributions to data has a long history and many different procedures have been advocated. Although models like normal, log-normal and gamma lead to a wide variety of distribution shapes, they do not provide the degree of generality that is frequently desirable (Hahn & Shapiro, 1967). To formally represent a set of data by an empirical distribution, Johnson (1949) derived a system of curves with the flexibility to cover a wide variety of shapes. Methods available to estimate the parameters of the Johnson distribution are discussed, and a new approach to estimate the four parameters of the Johnson family is proposed. The estimate makes use of both the maximum likelihood procedure and least square theory. The new MLE-Least Square approach is compared with other two commonly used methods. A simulation study shows that the MLE-Least square approach provides better results for SB , S>U and SL families.
关键词：Johnson distribution; unbouded; bounded; lognormal; estimation