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RobustANOVA  

Robust One-Way ANOVA Tests under Heteroscedasticity and Nonnormality
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("RobustANOVA", "0.3.0")



Attach the package and use:
library("RobustANOVA")
Maintained by
Gamze Guven
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-12
Latest Update: 2022-12-05
Description:
Robust tests (RW, RPB and RGF) are provided for testing the equality of several long-tailed symmetric (LTS) means when the variances are unknown and arbitrary. RW, RPB and RGF tests are robust versions of Welch's F test proposed by Welch (1951) , parametric bootstrap test proposed by Krishnamoorthy et. al (2007) ; and generalized F test proposed by Weerahandi (1995) ;, respectively. These tests are based on the modified maximum likelihood (MML) estimators proposed by Tiku(1967, 1968) , .
How to cite:
Gamze Guven (2022). RobustANOVA: Robust One-Way ANOVA Tests under Heteroscedasticity and Nonnormality. R package version 0.3.0, https://cran.r-project.org/web/packages/RobustANOVA. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2022-10-12 16:42), 0.2.0 (2022-11-09 15:10)
Other packages that cited RobustANOVA R package
View RobustANOVA citation profile
Other R packages that RobustANOVA depends, imports, suggests or enhances
Complete documentation for RobustANOVA
Functions, R codes and Examples using the RobustANOVA R package
Some associated functions: RGF . RPB . RW . peak_discharge . 
Some associated R codes: RGF.R . RPB.R . RW.R . param_estimates.R . peak_discharge.R .  Full RobustANOVA package functions and examples
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