maic

Calculate mAIC (modified Akaike Information Criterion).

Selecting linear and generalized linear models for large data sets
using modified stepwise procedure and modern selection criteria (like
modifications of Bayesian Information Criterion). Selection can be
performed on data which exceed RAM capacity. Bogdan et al., (2004)
<doi:10.1534/genetics.103.021683>.

Piotr Szulc

bigstep

Stepwise Selection for Large Data Sets

maic function

<dl><dt>loglik</dt>
<dd>A numeric, the log-likelihood.</dd>
<dt>k</dt>
<dd>An integer &gt;= 0, the number of selected variables.</dd>
<dt>p</dt>
<dd>An integer &gt; 0, the number of all variables or a weight.</dd>
<dt>const</dt>
<dd>A numeric &gt; 0, the expected number of significant variables.</dd></dl>

Arguments

mAIC — maic

<dl>

<dt>loglik</dt>
<dd>A numeric, the log-likelihood.</dd>


<dt>k</dt>
<dd>An integer &gt;= 0, the number of selected variables.</dd>


<dt>p</dt>
<dd>An integer &gt; 0, the number of all variables or a weight.</dd>


<dt>const</dt>
<dd>A numeric &gt; 0, the expected number of significant variables.</dd>

</dl>

maic: mAIC

Description

Usage

Value

Arguments

Examples