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

Performs the statistical test of Weibullness (Goodness-of-fit test for the Weibull distribution) using the sample correlation from the Weibull plot.

1 | ```
wp.test(x, a)
``` |

`x` |
a numeric vector of data values. Missing values are allowed, but the number of non-missing values must be between 3 and 1000. |

`a` |
the offset fraction to be used; typically in (0,1). See ppoints(). |

The Weibullness test is constructed using the sample correlation
which is calculated using the associated Weibull plot.
The critical value is then looked up in Weibull.Plot.Quantiles.
There is `print`

method for class `"htest"`

.

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. |

`sample.size` |
sample size (missing observations are deleted). |

`method` |
a character string indicating the Weibullness test. |

`data.name` |
a character string giving the name(s) of the data. |

Chanseok Park

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.

`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.

1 2 3 4 5 | ```
library(weibullness)
# For Weibullness hypothesis test.
x = rweibull(10, shape=1)
wp.test(x)
``` |

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