Assessing the goodness-of-fit of statistical distributions when data are grouped

被引:9
|
作者
Haschenburger, JK [1 ]
Spinelli, JJ
机构
[1] Univ Auckland, Sch Geog & Environm Sci, Auckland 1, New Zealand
[2] British Columbia Canc Agcy, Vancouver, BC V5Z 4E6, Canada
来源
MATHEMATICAL GEOLOGY | 2005年 / 37卷 / 03期
基金
加拿大自然科学与工程研究理事会;
关键词
Cramer-von Mises; Anderson-Darling; EDF statistics; Pearson chi-square; grouped exponential distribution;
D O I
10.1007/s11004-005-1558-0
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Modeling statistical distributions of phenomena can be compromised by the choice of goodness-of-fit statistics. The Pearson chi-square test is the most commonly used test in the geosciences, but the lesser known empirical distribution function (EDF) statistics should be preferred in many test situations. Using a data set from geomorphology, the Anderson-Darling test for grouped exponential distributions is employed to illustrate ease of use and statistical advantages of this EDF test. Attention to the issues discussed will result in more informed statistic selection and increased rigor in the identification of distribution functions that describe random variables.
引用
收藏
页码:261 / 276
页数:16
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