wp.test.pvalue: The p-value for the Weibullness Test

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

The p-value for the Weibullness Test

Description

Calculates the p-value for the Weibullness test which is based on the sample correlation from the Weibull plot.

Usage

wp.test.pvalue(r, n)

Arguments

r	the sample correlation coefficient from the Weibull plot; r is in (0,1).
n	the sample size.

Details

The p-value for the Weibullness test which is based on the sample correlation from the Weibull plot. There is print method for class "htest".

Value

A list with class "htest" containing the following components:

statistic	the value of the test statistic (sample correlation from the Weibull plot)
p.value	the p-value for the test.
method	a character string indicating the Weibullness test.

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

# p.value with r (sample correlation from the Weibull plot) and n (sample size).
wp.test.pvalue(r=0.6, n=10)

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