منابع مشابه
A Nonparametric Control Chart based on the Mann-Whitney Statistic
Nonparametric or distribution-free charts can be useful in statistical process control when there is limited knowledge about the underlying process. In this paper a Shewhart-type chart is considered for the location, based on the Mann-Whitney statistic. The control limit calculations use Lugannani-Rice saddlepoint, Edgeworth and other approximation methods along with Monte Carlo estimation and ...
متن کاملOptimizing Classi er Performance Via the Wilcoxon-Mann-Whitney Statistic
Cross entropy and mean squared error are typical cost functions used to optimize classi er performance. The goal of the optimization is usually to achieve the best correct classi cation rate. However, for many two-class real-world problems, the ROC curve is a more meaningful performance measure. We demonstrate that minimizing cross entropy or mean squared error does not necessarily maximize the...
متن کاملExploiting the Link Between the Wilcoxon-Mann-Whitney Test and a Simple Odds Statistic
Over a quarter-century ago, Alan Agresti (Biometrics, 1980) proposed using the generalized odds ratio (genOR) to summarize the association between two ordinal variables. Unfortunately, genOR is still largely unknown, even though it is elegantly straightforward and fills key voids in the working statistician’s toolbox. An extension of it, a statistic we are calling “WMWodds,” is an ideal effect-...
متن کاملA uniform saddlepoint expansion for the null-distribution of the Wilcoxon- Mann-Whitney statistic
The authors give the exact coefficient of 1/N in a saddlepoint approximation to the Wilcoxon-Mann-Whitney null-distribution. This saddlepoint approximation is obtained from an Edgeworth approximation to the exponentially tilted distribution. Moreover, the rate of convergence of the relative error is uniformly of order O(1/N) in a large deviation interval as defined in Feller (1971). The propose...
متن کاملOptimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However, for many real-world classification problems, the ROC curve is a more meaningful performance measure. We demonstrate that minimizing cross entropy or mean squared error does not necessarily maximize the area under the ...
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ژورنال
عنوان ژورنال: The Annals of Mathematical Statistics
سال: 1968
ISSN: 0003-4851
DOI: 10.1214/aoms/1177698142