SaemixModel-class

SaemixModel

[<-,SaemixModel-method

[,SaemixModel-method

initialize,SaemixModel-method

plot,SaemixModel-method

print,SaemixModel-method

showall,SaemixModel-method

show,SaemixModel-method

plot,SaemixModel

print,SaemixModel

showall,SaemixModel

show,SaemixModel

summary,SaemixModel

summary,SaemixModel-method

An object of the SaemixModel class, representing a non-linear mixed-effect model structure, used by the SAEM algorithm.

classes

The SAEM 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 (linearization, 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://software.monolix.org/).

Emmanuelle Comets

saemix

Stochastic Approximation Expectation Maximization (SAEM)
        algorithm

SaemixModel-class function

An object of the SaemixModel class can be created by using the function <code><a href="/link/saemixModel?package=saemix&version=0.96.1" rd-options="" data-mini-rdoc="saemix::saemixModel">saemixModel</a></code>

Objects from the Class

Class "SaemixModel"

SaemixModel-class: Class "SaemixModel"

Description

Arguments

Objects from the Class

References

See Also

Examples