EBEpair

Creates pairs plot of ETAs vs covariates with histograms and correlations.

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

EBEpair function

<dl><dt>tabEta</dt>
<dd>data.frame with ID, covariates, and ETA columns</dd>
<dt>RunNumber</dt>
<dd>character, model/run identifier</dd>
<dt>each</dt>
<dd>logical, if TRUE creates separate plots per covariate</dd></dl>

Arguments

EBE Pair Plot — EBEpair

<dl>

<dt>tabEta</dt>
<dd>data.frame with ID, covariates, and ETA columns</dd>


<dt>RunNumber</dt>
<dd>character, model/run identifier</dd>


<dt>each</dt>
<dd>logical, if TRUE creates separate plots per covariate</dd>

</dl>

EBEpair: EBE Pair Plot

Description

Usage

Arguments