npde.decorr.method

decorr.chol

decorr.inverse

decorr.polar

Specifies the method used to decorrelate observed and simulated data

methods

Provides routines to compute normalised prediction distribution errors, a metric designed to evaluate non-linear mixed effect models such as those used in pharmacokinetics and pharmacodynamics.

Emmanuelle Comets

npde

Normalised Prediction Distribution Errors for Nonlinear
Mixed-Effect Models

Karl Brendel

Thi Huyen Tram Nguyen

Marc Cerou

Romain Leroux

France Mentre

npde.decorr.method function

<dl><dt>x</dt>
<dd>a square matrix<dl>
 <dt>cholesky</dt>
<dd>decorrelation is performed through the Cholesky decomposition (default)</dd></dl></dd> <dt>inverse</dt>
<dd>decorrelation is performed by inverting Vi through the <code>eigen</code> function</dd> <dt>polar</dt>
<dd>the singular-value decomposition (<code>svd</code>) is used</dd> 
</dl>
 
@return This is not a function and does not have a return value, this is a statistical method.

Arguments

Decorrelation methods in npde — npde.decorr.method

<dl>

<dt>x</dt>
<dd>a square matrix<dl>
 <dt>cholesky</dt>
<dd>decorrelation is performed through the Cholesky decomposition (default)</dd>

 <dt>inverse</dt>
<dd>decorrelation is performed by inverting Vi through the <code>eigen</code> function</dd>

 <dt>polar</dt>
<dd>the singular-value decomposition (<code>svd</code>) is used</dd>

 
</dl>
 
@return This is not a function and does not have a return value, this is a statistical method.</dd>

</dl>

Decorrelation methods in npde

npde.decorr.method: Decorrelation methods in npde

Description

Arguments

Details

References