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Two modified Wilcoxon tests for symmetry about an unknown location parameter

未知位置参数下对称性的两种修正 Wilcoxon 检验

Two modifications of the Wilcoxon test for symmetry about the sample median are proposed and their large sample distribution theory derived. Their Pitman efficacies against contamination in the right tail are obtained. Both the asymptotic results and a Monte Carlo study show that the procedures are more powerful than the Wilcoxon test about the median against many asymmetric alternatives while preserving its robustness of level shown by Antille & Kersting (1977).

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A Scale-Free Goodness-Of-Fit Test for the Exponential Distribution Based on the Gini Statistic

基于 Gini 统计量的指数分布尺度无关拟合优度检验

Summary The sample Gini index is shown to be a powerful scale-free test of exponentiality against a variety of alternatives. Compared to the maximum likelihood test, the asymptotic relative efficiency of the Gini statistic is 0·69 against gamma and 0·88 against Weibull alternatives. Exact and asymptotic distribution theory is developed. On the basis of good power compared to competing tests, ease of computation, availability of exact critical values and robustness to…

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Small Sample Behavior of Some Robust Linear Estimators of Location

若干稳健线性位置估计量的小样本表现

Originally, Tukey justified the use of the trimmed mean as a robust estimator because of its high efficiency in large samples from contaminated normal data. The means, variances and covariances of the order statistics in small samples (of size ≤ 20) from a standard normal distribution contaminated by various fractions (.01, .05 and .10) of a normal distribution with mean 0 and scale parameter 3 are derived. The small sample behavior of various robust linear estimators is…

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The First-Median Test: A Two-Sided Version of the Control Median Test

第一中位数检验:控制中位数检验的双侧版本

Consider two independent samples (called x's and y's) of mutually independent observations from populations with c.d.f.'s F(x) and G(x) respectively. Let υ be the number of x's which are smaller than the median of the y-sample and let u be the number of y's which are less than the median of the x-sample. If the x-sample is regarded as the control group, then the control median test proposed by Kimball et al. [9], rejects the hypothesis that F(x) ≡ G(x) if u is small. The…

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