psi-methods

phi-methods

eta-methods

psi,SaemixObject-method

phi,SaemixObject-method

eta,SaemixObject-method

These methods are used to access estimates of individual parameters and random effects

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

psi-methods function

<dl class="dl-horizontal"><dt><code>signature(object = "SaemixObject")</code></dt><dd>please refer to the PDF documentation for the models</dd>
</dl>

Methods

Methods for Functions psi, phi and eta — psi-methods

Methods for Functions psi, phi and eta

psi-methods: Methods for Functions psi, phi and eta

Description

Arguments

Methods