weibull.test: Test for the Weibull distribution

In goft: Tests of Fit for some Probability Distributions

Description

Test for the Weibull distribution based on a data transformation to observations with type I extreme value (Gumbel) distribution.

Usage

weibull_test(x, method = "transf", N = 1000)

Arguments

x	numeric data vector containing a random sample of positive observations.
method	test to be used. So far, "transf" is the only option and it comes by default.
N	number of Monte Carlo samples used to approximate the p-value of the test. Default is N = 1000.

Details

The "ratio" test provided by function ev_test for the type I extreme value distribution is applied to the transformed observations.

Value

A list with class "htest" containing the following components.

statistic	the calculated value of the test statistic.
p.value	an approximated p-value of the test.
method	the character string "Test for the Weibull distribution".
data.name	a character string giving the name of the data set.

Author(s)

Elizabeth Gonzalez-Estrada, Jose A. Villasenor

See Also

Other tests for positive datasets are provided by functions ig_test, gamma_test and lnorm_test.

Examples

# Testing the Weibull distribution hypothesis on the maximum ozone levels given
# in the o3max data set.
data(o3max)
x <- o3max[ ,2]     # maximum ozone levels
weibull_test(x, N = 10000)     

Example output

Loading required package: fitdistrplus
Loading required package: MASS
Loading required package: survival
Loading required package: npsurv
Loading required package: lsei

	Test for the Weibull distribution

data:  x
p-value = 0.301

goft documentation built on July 1, 2020, 5:56 p.m.