
Testing for Stochastic Order in IntervalValued Data
We construct a procedure to test the stochastic order of two samples of ...
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NonParametric Cluster Significance Testing with Reference to a Unimodal Null Distribution
Cluster analysis is an unsupervised learning strategy that can be employ...
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New statistic for detecting laboratory effects in ORDANOVA
The present study defines a new statistic for detecting laboratory effec...
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Estimation of the weighted integrated square error of the Grenander estimator by the KolmogorovSmirnov statistic
We consider in this paper the Grenander estimator of unbounded, in gener...
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Comparing a Large Number of Multivariate Distributions
In this paper, we propose a test for the equality of multiple distributi...
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A HigherOrder KolmogorovSmirnov Test
We present an extension of the KolmogorovSmirnov (KS) twosample test, ...
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An outlierresistant indicator of anomalies among interlaboratory comparison data with associated uncertainty
A new robust pairwise statistic, the pairwise median scaled difference (...
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A comparison of Gap statistic definitions with and without logarithm function
The Gap statistic is a standard method for determining the number of clusters in a set of data. The Gap statistic standardizes the graph of (W_k), where W_k is the withincluster dispersion, by comparing it to its expectation under an appropriate null reference distribution of the data. We suggest to use W_k instead of (W_k), and to compare it to the expectation of W_k under a null reference distribution. In fact, whenever a number fulfills the original Gap statistic inequality, this number also fulfills the inequality of a Gap statistic using W_k, but not vice versa. The two definitions of the Gap function are evaluated on several simulated data sets and on a real data of DCEMR images.
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