| ev_test {goft} | R Documentation |
Tests for the extreme value distributions
Description
Correlation and ratio tests for Fisher-Tippet extreme value distributions.
Usage
ev_test(x, dist = "gumbel", method = "cor", N = 1000)
Arguments
x |
a numeric data vector containing a random sample. |
dist |
the extreme value distribution to be tested. Options are |
method |
the test to be used. Available options are |
N |
number of Monte Carlo samples used to approximate the p-value of the test when |
Details
Option "ratio" performs a test based on the ratio of two estimators for the variance of the Gumbel (type I extreme value) distribution (Gonzalez-Estrada and Villasenor, 2018).
Option "cor" performs a test based on the max-stability property of extreme value distributions (Gonzalez-Estrada and Villasenor, 2010). The sample size must lie between 20 and 250.
Value
A list with class "htest" containing the following components.
statistic |
the calculated value of the test statistic. |
p.value |
the approximated p-value of the test. |
method |
a character string for the method used to test the null hypothesis. |
data.name |
a character string giving the name of the data set. |
Author(s)
Elizabeth Gonzalez-Estrada, Jose A. Villasenor
References
Gonzalez-Estrada, E. and Villasenor, J.A. (2018). An R package for testing goodness of fit: goft. Journal of Statistical Computation and Simulation, 88 4, 726-751. https://doi.org/10.1080/00949655.2017.1404604
Gonzalez-Estrada, E. and Villasenor-Alva, J.A. (2010). A Goodness-of-Fit Test for Location-Scale Max-Stable Distributions. Communications in Statistics: Simulation and Computation, 39 3, 557-562. https://doi.org/10.1080/03610910903528293
Examples
# Example 1: testing the Gumbel distribution hypothesis using the correlation test
x <- -log(rexp(20)) # simulating a data set from the standard Gumbel distribution
ev_test(x)