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Journals / Hacettepe Journal of Mathematics and Statistics / 2018 / Cilt: 47 - Sayı: 4

A bootstrap test for symmetry based on quantiles

Vali ZARDASHT
Pages
1061–1069
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that the proposed test preserves its level and it has reasonable power properties on the family of distribution evaluated.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, we construct a nonparametric test for the symmetry assumption of an underling distribution based on the sample quantiles.
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Key Findings & Data:Bootstrap re-sampling from a symmetric empirical distribution function is used to obtain the p-value of the test.
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Conclusion & Impact:The results show that the proposed test preserves its level and it has reasonable power properties on the family of distribution evaluated.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Symmetry · Quantile · Test Power

Abstract

In this paper, we construct a nonparametric test for the symmetry assumption of an underling distribution based on the sample quantiles. Bootstrap re-sampling from a symmetric empirical distribution function is used to obtain the p-value of the test. The power of the new test statistic is compared with some well-known symmetry tests using a simulation study. The results show that the proposed test preserves its level and it has reasonable power properties on the family of distribution evaluated.

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Cite This Article

ZARDASHT, V. (2022). A bootstrap test for symmetry based on quantiles. Hacettepe Journal of Mathematics and Statistics, Cilt: 47 - Sayı: 4, 1061–1069. https://ajindex.com/articles/529866

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