Weibull.Plot.Quantiles

Quantiles for the Weibullness Test. They are obtained 
from the sample correlation from the Weibull plot. 
The number of Monte Carlo iterations is 1E08.Dataset representing the quantiles and the associated critical values for the Weibullness
test. They were obtained by conducting Monte Carlo simulations where the
sample correlation coefficients were calculated based on the Weibull plot. 
We used 1.0E08 Monte Carlo iterations in the simulation.

datasets

Weibull plot

Conducts a goodness-of-fit test for the Weibull distribution (referred to as the weibullness test) and furnishes parameter estimations for both the two-parameter and three-parameter Weibull distributions. Notably, the threshold parameter is derived through correlation from the Weibull plot. Additionally, this package conducts goodness-of-fit assessments for the exponential, Gumbel, and inverse Weibull distributions, accompanied by parameter estimations.
For more details, see Park (2017) <doi:10.23055/ijietap.2017.24.4.2848>,
Park (2018) <doi:10.1155/2018/6056975>, and Park (2023) <doi:10.3390/math11143156>.
This work was supported by the National Research Foundation of Korea (NRF) grants funded by
the Korea government (MSIT) (No. 2022R1A2C1091319, RS-2023-00242528).

Chanseok Park

weibullness

Goodness-of-Fit Test for Weibull Distribution (Weibullness)

Weibull.Plot.Quantiles function

This data frame contains 998 rows and 1001 columns.

Format

Quantiles for the Weibullness Test. They are obtained 
from the sample correlation from the Weibull plot. 
The number of Monte Carlo iterations is 1E08.

Dataset representing the quantiles and the associated critical values for the Weibullness
test. They were obtained by conducting Monte Carlo simulations where the
sample correlation coefficients were calculated based on the Weibull plot. 
We used 1.0E08 Monte Carlo iterations in the simulation.

Weibull.Plot.Quantiles: Weibull quantile values

Description

Usage

Arguments

Format

References