plot-methods

plot,ANY-method

Methods for function <code>plot</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

plot-methods function

<dl class="dl-horizontal"><dt><code>signature(x = "ANY")</code></dt><dd>default plot function ?</dd><dt><code>signature(x = "SaemixData")</code></dt><dd>Plots the data. Defaults to a spaghetti plot of response versus predictor, with lines joining the data for one individual.</dd><dt><code>signature(x = "SaemixModel")</code></dt><dd>Plots prediction of the model</dd><dt><code>signature(x = "SaemixObject")</code></dt><dd>This method gives access to a number of plots that can be performed on a SaemixObject</dd><dt><code>signature(x = "SaemixSimData")</code></dt><dd>Plots simulated datasets</dd>
</dl>

plot-methods: Methods for Function plot

Description

Arguments

Methods