On estimation of $$P\left( X  &gt; Y \right) $$PX&gt;Y based on judgement post stratification

Dastbaravarde, Ali; Zamanzade, Ehsan

doi:10.1007/s00362-017-0962-0

Cited by 3 publications

(2 citation statements)

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“…In this paper, we propose a new and easily motivated non-parametric test with competitive performance and straightforward interpretation. Based on the non-parametric relative effect, a quantity that has received renewed attention lately, due to its favorable properties, see Brunner et al (2018) or Dastbaravarde and Zamanzade (2017), the test concentrates on an easy interpretation. Using the approach of Parkinson et al (2018), we propose a fully non-parametric testing method that can easily be performed using ranks.…”

Section: Introductionmentioning

confidence: 99%

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Testing for equality of distributions using the concept of (niche) overlap

Parkinson-Schwarz

Bathke

2021

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In this paper, we propose a new non-parametric test for equality of distributions. The test is based on the recently introduced measure of (niche) overlap and its rank-based estimator. As the estimator makes only one basic assumption on the underlying distribution, namely continuity, the test is universal applicable in contrast to many tests that are restricted to only specific scenarios. By construction, the new test is capable of detecting differences in location and scale. It thus complements the large class of rank-based tests that are constructed based on the non-parametric relative effect. In simulations this new test procedure obtained higher power and lower type I error compared to two common tests in several settings. The new procedure shows overall good performance. Together with its simplicity, this test can be used broadly.

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Section: Introductionmentioning

confidence: 99%

“…Based on the non-parametric relative effect, a quantity that has received renewed attention lately, due to its favorable properties, see Brunner et al. ( 2018 ) or Dastbaravarde and Zamanzade ( 2017 ), the test concentrates on an easy interpretation. Using the approach of Parkinson et al.…”

Section: Introductionmentioning

confidence: 99%