summary-methods

summary,ANY-method

Methods for function <code>summary</code>

methods

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/).

summary-methods: Methods for Function summary

Description

Arguments