lnorm_test {goft} | R Documentation |
Test for the lognormal distribution
Description
Test for the lognormal distribution based on a data transformation to normal observations.
Usage
lnorm_test(x)
Arguments
x |
a numeric data vector containing a random sample of positive observations. |
Details
Shapiro-Wilk test is used for testing normality on 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 lognormal distribution based on a transformation to normality". |
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 some alternative distributions to the lognormal model are impremented in functions ig_test
, gamma_test
and weibull_test
.
Examples
# Testing the lognormal distribution hypothesis on the compressive strength variable
# of the strength data set.
data("strength")
x <- strength$cstrength # compressive strength
lnorm_test(x) # testing the lognormal distribution hypothesis
[Package goft version 1.3.6 Index]