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)