makeCOVbin

Discretise numeric value into a categorical variable using 
the user-defined breaks. If cutoffs and the number of bins (K) is NULL, 
find the best number of bins using the optK function and find the best 
cutoff values using the FindBestCut function.

Various visual and numerical diagnosis methods for the nonlinear mixed effect model, including visual predictive checks, numerical predictive checks, and coverage plots (Karlsson and Holford, 2008, <https://www.page-meeting.org/?abstract=1434>).

Eun-Kyung Lee

nlmeVPC

Visual Model Checking for Nonlinear Mixed Effect Model

Eun-Hwa Kang

makeCOVbin function

<dl><dt>X</dt>
<dd>A numeric vector corresponding to Y.</dd>
<dt>K</dt>
<dd>Number of bins.</dd>
<dt>cutoffs</dt>
<dd>A numeric vector of two or more unique cut points.</dd>
<dt>adjust0bin</dt>
<dd>Adjust bin with 0 observation if TRUE.</dd>
<dt>...</dt>
<dd>Arguments to be passed to methods.</dd></dl>

Arguments

Discretise numeric data into categorical data — makeCOVbin

<dl>

<dt>X</dt>
<dd>A numeric vector corresponding to Y.</dd>


<dt>K</dt>
<dd>Number of bins.</dd>


<dt>cutoffs</dt>
<dd>A numeric vector of two or more unique cut points.</dd>


<dt>adjust0bin</dt>
<dd>Adjust bin with 0 observation if TRUE.</dd>


<dt>...</dt>
<dd>Arguments to be passed to methods.</dd>

</dl>

makeCOVbin: Discretise numeric data into categorical data

Description

Usage

Value

Arguments

References

Examples