[&lt;--methods

Methods for function <code>[&lt;-</code>, to allow replacements of the value of an element within an S4 object

methods

The SAEMIX package implements the Stochastic Approximation EM algorithm for parameter estimation in (non)linear mixed effects models. The SAEM algorithm: - 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, - provides standard errors for the maximum likelihood estimator - estimates the conditional modes, the conditional means and the conditional standard deviations of the individual parameters, using the Hastings-Metropolis algorithm. Several applications of SAEM in agronomy, animal breeding and PKPD analysis have been published by members of the Monolix group (<http://group.monolix.org/>).

Emmanuelle Comets

saemix

Stochastic Approximation Expectation Maximization (SAEM)
Algorithm

[&lt;--methods function

<dl class="dl-horizontal"><dt><code>signature(x = "SaemixData")</code></dt><dd>replace elements of an object SaemixData</dd><dt><code>signature(x = "SaemixModel")</code></dt><dd>replace elements of an object SaemixModel</dd><dt><code>signature(x = "SaemixObject")</code></dt><dd>replace elements of an object SaemixObject</dd><dt><code>signature(x = "SaemixRepData")</code></dt><dd>replace elements of an object SaemixRepData</dd><dt><code>signature(x = "SaemixRes")</code></dt><dd>replace elements of an object SaemixRes</dd><dt><code>signature(x = "SaemixSimData")</code></dt><dd>replace elements of an object SaemixSimData</dd>
</dl>

[<--methods: Methods for "set" Function [<-

Description

Arguments

Methods