lnorm.test: Test for the lognormal distribution
In goft: Tests of Fit for some Probability Distributions

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

Test for the lognormal distribution based on a data transformation to normal observations.

1	lnorm_test(x)

`x`	a numeric data vector containing a random sample of positive observations.

Shapiro-Wilk test is used for testing normality on the transformed observations.

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.

Elizabeth Gonzalez-Estrada, Jose A. Villasenor

Other tests for some alternative distributions to the lognormal model are impremented in functions ig_test, gamma_test and weibull_test.

# 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

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

	Test for the lognormal distribution based on a transformation to
	normality

data:  x
p-value = 0.3734