weibullness (version 1.23.8)

wp.test.pvalue: 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)

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.

Arguments

r

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

n

the sample size.

Author

Chanseok Park

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".

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.
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

library(weibullness)

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