NORMALITY TRANSFORMATIONS FOR ENVIRONMENTAL DATA FROM COMPOUND NORMAL-LOGNORMAL DISTRIBUTIONS

被引：12

作者：

BLACKWOOD, LG

机构：

[1] Idaho National Engineering Laboratory, Idaho Falls, ID, 83415

来源：

ENVIRONMENTAL MONITORING AND ASSESSMENT | 1995年 / 35卷 / 01期

关键词：

D O I：

10.1007/BF02396410

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The combination of lognormally distributed quantities of interest with normally distributed random measurement error produces data that follow a compound normal-lognormal (NLN) distribution. When the measurement error is large enough, such data do not approximate normality, even after a logarithmic transformation. This paper reports the results of a search for a transformation method for NLN data that is not only technically appropriate, but easy to implement as well. Three transformation families were found to work relatively well. These families are compared in terms of success in achieving normality and robustness, using simulated NLN data and actual environmental data believed to follow a NLN distribution. The exponential family of transformations was found to give the best overall results.

引用

页码：55 / 75

页数：21

共 14 条

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