| gp.test.pvalue {weibullness} | R Documentation |
The p-value for the Gumbel goodness-of-Fit Test
Description
Calculates the p-value for the Gumbel goodness-of-fit test which is based on the sample correlation from the Gumbel probability plot.
Usage
gp.test.pvalue(r, n)
Arguments
r |
the sample correlation coefficient from the Gumbel probability plot; r is in (0,1). |
n |
the sample size. |
Details
The p-value for the Gumbel goodness-of-fit test which is based on
the sample correlation from the Gumbel probability 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 Gumbel probability plot) |
p.value |
the p-value for the test. |
method |
a character string indicating the Gumbel goodness-of-fit test. |
Author(s)
Chanseok Park
References
Kinnison, R. (1989). Correlation Coefficient Goodness-of-Fit Test for the Extreme-Value Distribution. The American Statistician, 43(2), 98-100.
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.
wp.test for performing the Weibullness test.
shapiro.test for performing the Shapiro-Wilk test for normality.
Examples
# p.value with r (sample correlation from the Gumbel probability plot) and n (sample size).
gp.test.pvalue(r=0.98504, n=10)