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

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

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

Usage

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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.
http://journals.sfu.ca/ijietap/index.php/ijie/article/view/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

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library(weibullness)

# 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 Aug. 19, 2019, 9:02 a.m.