predict-methods

predict,ANY-method

Methods for function <code>predict</code>

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

predict-methods function

<dl class="dl-horizontal"><dt><code>signature(object = "ANY")</code></dt><dd>Default predict functions</dd><dt><code>signature(object = "SaemixObject")</code></dt><dd>Computes predictions using the results of an SAEM fit</dd>
</dl>

predict-methods: Methods for Function predict

Description

Arguments

Methods