plot,SaemixModel-method

plot,SaemixModel-methods

plot,SaemixModel

an SaemixData object or an SaemixSimData object

unused, present for compatibility with base plot function

range of X over which the model is to be plotted

range

additional predictors needed to pass on to the model

predictors

additional arguments to be passed on to plot (titles, legends, ...)

This function will plot predictions obtained from an SaemixModel object over a given range of X. Additional predictors may be passed on to the function using the predictors argument.

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. Documentation about 'saemix' is provided by a comprehensive user guide in the inst folder, and a reference concerning the methods is the paper by Comets, Lavenu and Lavielle (2017, <doi:10.18637/jss.v080.i03>). See 'citation("saemix")' for details.

plot,SaemixModel-method: Plot model predictions using an SaemixModel object

Description

Usage

Arguments