run.p

Calculates P(Run count &lt;= r | m, n) for the runs test.

internal

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

run.p function

<dl><dt>m</dt>
<dd>count of fewer species (minimum value = 0)</dd>
<dt>n</dt>
<dd>count of more frequent species (minimum value = 1)</dd>
<dt>r</dt>
<dd>count of runs (minimum value = 1)</dd></dl>

Arguments

Run Test Probability — run.p

<dl>

<dt>m</dt>
<dd>count of fewer species (minimum value = 0)</dd>


<dt>n</dt>
<dd>count of more frequent species (minimum value = 1)</dd>


<dt>r</dt>
<dd>count of runs (minimum value = 1)</dd>

</dl>

run.p: Run Test Probability

Description

Usage

Value

Arguments