plot.MTest

Plot density or empirical cumulative distribution from <code>Bvals</code> in <code>MTest output</code>.

MTest

Functions for detecting multicollinearity. This test gives statistical support to two of the most famous methods for detecting multicollinearity in applied work: Klein’s rule and Variance Inflation Factor (VIF). See the URL for the papers associated with this package, as for instance, Morales-Oñate and Morales-Oñate (2015) <doi:10.33333/rp.vol51n2.05>.

V<c3><ad>ctor Morales-O<c3><b1>ate

A Procedure for Multicollinearity Testing using Bootstrap

Víctor Morales-Oñate

Bolívar Morales-Oñate

plot.MTest function

<dl>
 <dt>x</dt>
<dd>an object of the class <code>"MTest"</code></dd> <dt>type</dt>
<dd>Numeric; 1 if density, 2 if ecdf plot is returned</dd> <dt>plotly</dt>
<dd>Logical; if <code>FALSE</code>, a <code>ggplotly</code> plot is returned</dd> <dt>...</dt>
<dd>other arguments to be passed to the function
 <code>ggplot</code></dd></dl>

Arguments

Plot density or empirical cumulative distribution from MTest — plot.MTest

<dl>


 <dt>x</dt>
<dd>an object of the class <code>"MTest"</code></dd>

 <dt>type</dt>
<dd>Numeric; 1 if density, 2 if ecdf plot is returned</dd>

 <dt>plotly</dt>
<dd>Logical; if <code>FALSE</code>, a <code>ggplotly</code> plot is returned</dd>

 <dt>...</dt>
<dd>other arguments to be passed to the function
 <code>ggplot</code></dd>

</dl>

plot.MTest: Plot density or empirical cumulative distribution from MTest

Description

Usage

Value

Arguments

Details

See Also