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RobustBF  

Robust Solution to the Behrens-Fisher Problem
View on CRAN: Click here


Download and install RobustBF package within the R console
Install from CRAN:
install.packages("RobustBF")

Install from Github:
library("remotes")
install_github("cran/RobustBF")

Install by package version:
library("remotes")
install_version("RobustBF", "0.2.0")



Attach the package and use:
library("RobustBF")
Maintained by
Gamze Guven
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-01
Latest Update: 2021-11-15
Description:
Robust tests (RW and RF) are provided for testing the equality of two long-tailed symmetric (LTS) means when the variances are unknown and arbitrary. RW test is a robust version of Welch's two sample t test and the RF is a robust fiducial based test. The RW and RF tests are proposed using the adaptive modified maximum likelihood (AMML) estimators derived by Tiku and Surucu (2009) and Donmez (2010) .
How to cite:
Gamze Guven (2021). RobustBF: Robust Solution to the Behrens-Fisher Problem. R package version 0.2.0, https://cran.r-project.org/web/packages/RobustBF. Accessed 22 Sep. 2026.
Previous versions and publish date:
(2026-07-09 08:23), 0.1.0 (2021-07-01 09:30)
Other packages that cited RobustBF R package
View RobustBF citation profile
Other R packages that RobustBF depends, imports, suggests or enhances
Complete documentation for RobustBF
Functions, R codes and Examples using the RobustBF R package
Some associated functions: RF . RW . 
Some associated R codes: RF.R . RW.R . calc_estimates.R .  Full RobustBF package functions and examples
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