A comparative simulation of multiple testing procedures in circular data problems

Feridun Tasdan and Ozgur Yeniay

Journal of Applied Statistics, 2018, vol. 45, issue 2, 255-269

Abstract: Bonferroni correction procedures are commonly used for performing multiple hypothesis tests in linear data problems. Moreover, several improved Bonferroni type procedures have been proposed and shown that they attain a type-I error rate $ (\alpha ) $ (α) better than the classical Bonferroni approach, but all of the studies are considered for linear data problems. The circular data analysis is a developing field of statistics that lacks similar studies, and also lacks computer programs to implement Bonferroni procedures. The aim of this study is to perform a comparative study of improved Bonferroni procedures and also to provide a computer program in R that performs classical and improved Bonferroni procedures for circular data problems.

Date: 2018
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DOI: 10.1080/02664763.2016.1273886

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