SaemixObject-class: Class "SaemixObject"

In saemix: Stochastic Approximation Expectation Maximization (SAEM) Algorithm

Class "SaemixObject"

Description

An object of the SaemixObject class, storing the input to saemix, and the results obtained by a call to the SAEM algorithm

Details

Details of the algorithm can be found in the pdf file accompanying the package.

Objects from the Class

An object of the SaemixObject class is created after a call to saemix and contain the following slots:

data:

Object of class "SaemixData": saemix dataset, created by a call to saemixData

model:

Object of class "SaemixModel": saemix model, created by a call to saemixModel

results:

Object of class "SaemixData": saemix dataset, created by a call to saemixData

rep.data:

Object of class "SaemixRepData": (internal) replicated saemix dataset, used the execution of the algorithm

sim.data:

Object of class "SaemixSimData": simulated saemix dataset

options:

Object of class "list": list of settings for the algorithm

prefs:

Object of class "list": list of graphical options for the graphs

Methods

[<-

signature(x = "SaemixObject"): replace elements of object

[

signature(x = "SaemixObject"): access elements of object

initialize

signature(.Object = "SaemixObject"): internal function to initialise object, not to be used

plot

signature(x = "SaemixObject"): plot the data

print

signature(x = "SaemixObject"): prints details about the object (more extensive than show)

showall

signature(object = "SaemixObject"): shows all the elements in the object

show

signature(object = "SaemixObject"): prints details about the object

summary

signature(object = "SaemixObject"): summary of the object. Returns a list with a number of elements extracted from the object.

Author(s)

Emmanuelle Comets [e-mail]

Audrey Lavenu

Marc Lavielle.

References

E Comets, A Lavenu, M Lavielle M (2017). Parameter estimation in nonlinear mixed effect models using saemix, an R implementation of the SAEM algorithm. Journal of Statistical Software, 80(3):1-41.

E Kuhn, M Lavielle (2005). Maximum likelihood estimation in nonlinear mixed effects models. Computational Statistics and Data Analysis, 49(4):1020-1038.

E Comets, A Lavenu, M Lavielle (2011). SAEMIX, an R version of the SAEM algorithm. 20th meeting of the Population Approach Group in Europe, Athens, Greece, Abstr 2173.

See Also

SaemixData SaemixModel saemixControl saemix plot.saemix,

Examples

showClass("SaemixObject")

saemix documentation built on May 29, 2024, 10:43 a.m.