| wp.test.pvalue {weibullness} | R Documentation |
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.
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)