Lilliefors_test

Performs the Lilliefors normality test, which is an empirical distribution
function (EDF)-based goodness-of-fit test derived from the Kolmogorov–Smirnov
test, using the approximation proposed by Molin and Abdi (1998).

A toolkit for assessing data normality using a comprehensive collection of statistical methods.
It includes descriptive measures and formal hypothesis tests, such as skewness and kurtosis tests,
the Anderson–Darling test, the Shapiro–Wilk test, and the D'Agostino–Pearson K2 omnibus test.

Joon-Keat Lai

normality

Tests for Departure from Normality

Lilliefors_test function

<dl><dt>x</dt>
<dd>A numeric vector, at least length of 8.</dd>
<dt>alpha</dt>
<dd>Numeric (default: 0.05). Significance threshold, range from 0 to 1.</dd>
<dt>silent</dt>
<dd>Logical (default: FALSE). If <code>FALSE</code>, print out the results.</dd>
<dt>summary</dt>
<dd>Logical (default: TRUE). Produce a summary table.</dd>
<dt>misc</dt>
<dd>Logical (default: FALSE). Output other unimportant parameters.</dd></dl>

Arguments

Lilliefors Normality Test — Lilliefors_test

<dl>

<dt>x</dt>
<dd>A numeric vector, at least length of 8.</dd>


<dt>alpha</dt>
<dd>Numeric (default: 0.05). Significance threshold, range from 0 to 1.</dd>


<dt>silent</dt>
<dd>Logical (default: FALSE). If <code>FALSE</code>, print out the results.</dd>


<dt>summary</dt>
<dd>Logical (default: TRUE). Produce a summary table.</dd>


<dt>misc</dt>
<dd>Logical (default: FALSE). Output other unimportant parameters.</dd>

</dl>

Lilliefors_test: Lilliefors Normality Test

Description

Usage

Value

Arguments

References

Examples