iwp.test.critical: Critical Value for the inverse Weibullness Test

In weibullness: Goodness-of-Fit Test for Weibull Distribution (Weibullness)

Critical Value for the inverse Weibullness Test

Description

Calculates the critical value for the inverse Weibullness test

Usage

iwp.test.critical(alpha, n)

Arguments

alpha	the significance level.
n	the sample size.

Details

This function calculates the critical value for the inverse Weibullness test which is constructed using the sample correlation from the associated inverse Weibull plot. The critical value is then looked up in IW.Plot.Quantiles. There is print method for class "iwp.test.critical".

Value

A list with class "iwp.test.critical" containing the following components:

sample.size	sample size (missing observations are deleted).
alpha	significance level.
critical.value	critical value.
data.name	a character string giving the name(s) of the data.

Author(s)

Chanseok Park

References

Park, C. (2017). Weibullness test and parameter estimation of the three-parameter Weibull model using the sample correlation coefficient. International Journal of Industrial Engineering - Theory, Applications and Practice, 24(4), 376-391.
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.23055/ijietap.2017.24.4.2848")}

Vogel, R. M. and C. N. Kroll (1989). Low-Flow Frequency Analysis Using Probability-Plot Correlation Coefficients. Journal of Water Resources Planning and Management, 115, 338-357.

See Also

ks.test for performing the Kolmogorov-Smirnov test for the goodness of fit test of two samples.

shapiro.test for performing the Shapiro-Wilk test for normality.

Examples

# Critical value with alpha (significance level) and n (sample size).
iwp.test.critical(alpha=0.01, n=10)

weibullness documentation built on May 29, 2024, 1:27 a.m.