A minimum distance estimation approach to the two-sample location-scale problem.
As reported by Kalbfleisch and Prentice (1980), the generalized Wilcoxon test fails to detect a difference between the lifetime distributions of the male and female mice died from Thymic Leukemia. This failure is a result of the test's inability to detect a distributional difference when a location shift and a scale change exist simultaneously. In this article, we propose an estimator based on the minimization of an average distance between two independent quantile processes under a location-scale model. Large sample inference on the proposed estimator, with possible right-censorship, is discussed. The mouse leukemia data are used as an example for illustration purpose.
Zhang
Zhiyi
Z
Department of Mathematics, University of North Carolina at Charlotte, NC 28223, USA.
Yu
Qiqing
Q
D000818:Animals; D003627:Data Interpretation, Statistical; D005260:Female; D007942:Leukemia, Experimental / Q000401:mortality; D008297:Male; D051379:Mice; D015233:Models, Statistical; D018709:Statistics, Nonparametric; D016019:Survival Analysis; D013953:Thymus Neoplasms / Q000401:mortality; D014481:United States