SumOut

Scans subdirectories matching RunExt and collects summary metrics
for model development flow analysis.

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

SumOut function

<dl><dt>FileExt</dt>
<dd>character, control file extension</dd>
<dt>RunExt</dt>
<dd>character, run folder extension</dd>
<dt>OutExt</dt>
<dd>character, output file extension</dd></dl>

Arguments

Summarize Multiple NONMEM Runs — SumOut

<dl>

<dt>FileExt</dt>
<dd>character, control file extension</dd>


<dt>RunExt</dt>
<dd>character, run folder extension</dd>


<dt>OutExt</dt>
<dd>character, output file extension</dd>

</dl>

SumOut: Summarize Multiple NONMEM Runs

Description

Usage

Value

Arguments