resid.saemix

resid.SaemixRes

residuals.SaemixRes

residuals.saemix

residuals

resid

resid.SaemixObject

residuals.SaemixObject

residuals is a generic function which extracts model residuals from objects returned by modelling functions. The abbreviated form resid is an alias for residuals

methods

The 'saemix' package implements the Stochastic Approximation EM algorithm for parameter estimation in (non)linear mixed effects models. The SAEM algorithm (i) computes the maximum likelihood estimator of the population parameters, without any approximation of the model (linearisation, quadrature approximation,...), using the Stochastic Approximation Expectation Maximization (SAEM) algorithm, (ii) provides standard errors for the maximum likelihood estimator (iii) estimates the conditional modes, the conditional means and the conditional standard deviations of the individual parameters, using the Hastings-Metropolis algorithm (see Comets et al. (2017) <doi:10.18637/jss.v080.i03>). Many applications of SAEM in agronomy, animal breeding and PKPD analysis have been published by members of the Monolix group. The full PDF documentation for the package including references about the algorithm and examples can be downloaded on the github of the IAME research institute for 'saemix': <https://github.com/iame-researchCenter/saemix/blob/7638e1b09ccb01cdff173068e01c266e906f76eb/docsaem.pdf>.

Emmanuelle Comets

saemix

Stochastic Approximation Expectation Maximization (SAEM)
Algorithm

Audrey Lavenu

Marc Lavielle

Belhal Karimi

Maud Delattre

Marilou Chanel

Johannes Ranke

Sofia Kaisaridi

Lucie Fayette

resid.saemix function

<dl><dt>object</dt>
<dd>an SaemixRes or an SaemixObject object</dd>
<dt>type</dt>
<dd>string determining which residuals are extracted. Possible values are: "ires" (individual residuals, default), "wres" (weighted population residuals), "npde" (normalised prediction distribution errors), "pd" (prediction discrepancies), "iwres" (individual weighted residuals) and "icwres" (conditional individual weighted residuals). See user guide for details.</dd>
<dt>...</dt>
<dd>further arguments to be passed to or from other methods</dd></dl>

Arguments

Extract Model Residuals — resid.saemix

<dl>

<dt>object</dt>
<dd>an SaemixRes or an SaemixObject object</dd>


<dt>type</dt>
<dd>string determining which residuals are extracted. Possible values are: "ires" (individual residuals, default), "wres" (weighted population residuals), "npde" (normalised prediction distribution errors), "pd" (prediction discrepancies), "iwres" (individual weighted residuals) and "icwres" (conditional individual weighted residuals). See user guide for details.</dd>


<dt>...</dt>
<dd>further arguments to be passed to or from other methods</dd>

</dl>

Extract Model Residuals

resid.saemix: Extract Model Residuals

Description

Usage

Value

Arguments