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arXiv · 1806.10947

Extremely efficient permutation and bootstrap hypothesis tests using R

Christina Chatzipantsiou·Marios Dimitriadis·Manos Papadakis·Michail Tsagris
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Abstract

Re-sampling based statistical tests are known to be computationally heavy, but reliable when small sample sizes are available. Despite their nice theoretical properties not much effort has been put to make them efficient. In this paper we treat the case of Pearson correlation coefficient and two independent samples t-test. We propose a highly computationally efficient method for calculating permutation based p-values in these two cases. The method is general and can be applied or be adopted to other similar two sample mean or two mean vectors cases.

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Christina Chatzipantsiou, Marios Dimitriadis, Manos Papadakis, Michail Tsagris. 2018-06-28. Extremely efficient permutation and bootstrap hypothesis tests using R. https://arxiv.org/abs/1806.10947

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