Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13087/3247
Title: RobustBF: An R Package for Robust Solution to the Behrens-Fisher Problem
Authors: Güven, Gamze
Acıtaş, Şükrü
Samkar, Hatice
Şenoğlu, Birdal
Keywords: Population Variances
Parameters
Issue Date: 2021
Publisher: R Foundation Statistical Computing
Abstract: Welch's two-sample t-test based on least squares (LS) estimators is generally used to test the equality of two normal means when the variances are not equal. However, this test loses its power when the underlying distribution is not normal. In this paper, two different tests are proposed to test the equality of two long-tailed symmetric (LTS) means under heterogeneous variances. Adaptive modified maximum likelihood (AMML) estimators are used in developing the proposed tests since they are highly efficient under LTS distribution. An R package called RobustBF is given to show the implementation of these tests. Simulated Type I error rates and powers of the proposed tests are also given and compared with Welch's t-test based on LS estimators via an extensive Monte Carlo simulation study.
URI: https://hdl.handle.net/20.500.13087/3247
ISSN: 2073-4859
Appears in Collections:İstatistik Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
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