ResTest

Tests whether residual counts at various Z-value thresholds follow
expected binomial distributions.

This shows how NONMEM(R) software works. NONMEM's classical
estimation methods like 'First Order(FO) approximation', 'First Order
Conditional Estimation(FOCE)', and 'Laplacian approximation' are explained.
Additionally, provides functions for post-run processing of NONMEM output
files, generating comprehensive PDF diagnostic reports including objective
function value analysis, parameter estimates, prediction diagnostics,
residual diagnostics, empirical Bayes estimate (EBE) analysis, input data
summary, and individual pharmacokinetic parameter distributions.

Kyun-Seop Bae

Understanding Nonlinear Mixed Effects Modeling for Population
Pharmacokinetics

ResTest function

<dl><dt>ResTab</dt>
<dd>data.frame with residual columns</dd>
<dt>TestCols</dt>
<dd>character vector of column names to test</dd>
<dt>ZVals</dt>
<dd>numeric vector of Z-value thresholds</dd>
<dt>PctVals</dt>
<dd>numeric vector of percentile values</dd></dl>

Arguments

Residual Count Test Using Binomial Distribution — ResTest

<dl>

<dt>ResTab</dt>
<dd>data.frame with residual columns</dd>


<dt>TestCols</dt>
<dd>character vector of column names to test</dd>


<dt>ZVals</dt>
<dd>numeric vector of Z-value thresholds</dd>


<dt>PctVals</dt>
<dd>numeric vector of percentile values</dd>

</dl>

ResTest: Residual Count Test Using Binomial Distribution

Description

Usage

Value

Arguments