Log-Normal Versus Gamma Models for Analyzing Data from Quality-Improvement Experiments

被引:14
|
作者
Das, Rabindra Nath [2 ]
Lee, Youngjo [1 ]
机构
[1] Seoul Natl Univ, Dept Stat, Seoul 151747, South Korea
[2] Univ Burdwan, Dept Stat, Burdwan 713104, W Bengal, India
关键词
joint generalized linear model; multiplicative model; non-constant coefficient of variation; structured dispersion; UNIFIED APPROACH;
D O I
10.1080/08982110802317372
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Recently, log-normal and gamma models are of interest in fitting data arising from quality-improvement experiments. It is known that the gamma model with the constant coefficient of variation and the log-normal model with constant variance often give similar analyzes. However, in the analysis of data from quality improvement experiments, neither the coefficient of variation nor the variance needs to be constant, so that the two models do not necessarily give similar results. A choice needs to be made between the gamma and the log-normal models.
引用
收藏
页码:79 / 87
页数:9
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