| RPB {RobustANOVA} | R Documentation | 
Robust Parametric Bootstrap Test based on MML estimators
Description
Computes the p-value of the robust parametric bootstrap (RPB) test for the equality of means of several long-tailed symmetric (LTS) distributions when the variances are unknown and arbitrary.
Usage
RPB(formula, data, alpha , verbose = TRUE, p_shape, repn)
Arguments
| formula | a formula of the form left-hand-side | 
| data | data frame containing the variables in the formula. | 
| alpha | the level of significance. Default is set to alpha = 0.05. | 
| verbose | a logical for printing output to R console. | 
| p_shape | shape parameter of the LTS distribution. | 
| repn | replication number for performing the  | 
Details
RPB test based on modifed maximum likelihood (MML) estimators is proposed as a robust alternative to parametric bootstrap (PB) test proposed by Krishnamoorthy et. al (2007). See also Tiku (1967, 1968) for the details of MML estimators. The p-value for the RPB test is based on the replication number in the algorithm given by Guven et. al (2022).
Value
A list with class "htest" containing the following components:
| p.value | the p-value for the  | 
| alpha | the level of significance. | 
| method | a character string "Robust Parametric Bootstrap Test based on MML Estimators" indicating which test is used. | 
| data | a data frame containing the variables. | 
| formula | a formula of the form left-hand-side | 
Author(s)
Gamze Guven <gamzeguven@ogu.edu.tr>
References
G. Guven, S. Acitas, and B. Senoglu, B. RobustANOVA: An R Package for one-way ANOVA under heteroscedasticity and nonnormality. Under review, 2022.
K. Krishnamoorthy, F. Lu, and T. Mathew. A parametric bootstrap approach for anova with unequal variances: Fixed and random models. Computational Statistics & Data Analysis, 51(12): 5731-5742,2007.
M. L. Tiku. Estimating the mean and standard deviation from a censored normal sample. Biometrika, 54:155-165, 1967.
M. L. Tiku. Estimating the parameters of log-normal distribution from censored samples. Journal of the American Statistical Association, 63(321): 134-140, 1968.
Examples
library(RobustANOVA)
RPB(obs ~ methods, data = peak_discharge, alpha = 0.05, verbose = TRUE, p_shape=2.3, repn=5000)