show-methods

Prints a short summary of an 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

show-methods function

<dl class="dl-horizontal"><dt><code>signature(x = "ANY")</code></dt><dd>Default show function</dd><dt><code>signature(x = "SaemixData")</code></dt><dd>Prints a short summary of a SaemixData object</dd><dt><code>signature(x = "SaemixModel")</code></dt><dd>Prints a short summary of a SaemixModel object</dd><dt><code>signature(x = "SaemixObject")</code></dt><dd>Prints a short summary of the results from a SAEMIX fit</dd><dt><code>signature(x = "SaemixRes")</code></dt><dd>Not user-level</dd><dt><code>signature(object = "SaemixRepData")</code></dt><dd>Prints a short summary of a SaemixRepData object</dd><dt><code>signature(object = "SaemixSimData")</code></dt><dd>Prints a short summary of a SaemixSimData object</dd>
</dl>

show-methods: Methods for Function show

Description

Arguments

Methods