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REMixed (version 1.1.2)

Regularized Estimation in Mixed Effects Model

Description

Implementation of an algorithm in two steps to estimate parameters of a model whose latent dynamics are inferred through latent processes, jointly regularized. This package uses 'Monolix' software (), which provide robust statistical method for non-linear mixed effects modeling. 'Monolix' must have been installed prior to use.

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Version

Install

install.packages('REMixed')

Monthly Downloads

257

Version

1.1.2

License

GPL (>= 3)

Maintainer

Auriane Gabaut

Last Published

January 19th, 2026

Functions in REMixed (1.1.2)

plotCalibration

Calibration plot
plotConvergence

Log-likelihood convergence
retrieveBest

REMixed results
plotSAEM

Display the value of parameters at each iteration
readMLX

Extract Data for REMixed Algorithm from a Monolix Project
plotIC

IC plot
plotInit

Plot initialization
remix

REMixed algorithm
AIC.remix

AIC for remix object
dynFUN_demo

Dynamic functions demo
BICc

BICc
eBIC

eBIC
BIC.remix

BIC for remix object
computeFinalTest

Compute final estimation
getMLXdir

Get monolix demo project path
extract

extract remix results from cvRemix object
cv.remix

REMixed algorithm over a grid of \(\lambda\)
model.pk

Generate trajectory of PK model
plot.cvRemix

Plot of cv.remix object
model.clairon

Model from Clairon and al.,2023
model.pasin

Model from Pasin and al.,2019
gh.LL

Adaptive Gauss-Hermite approximation of log-likelihood derivatives
initStrat

Initialization strategy
indParm

Generate individual parameters
REMixed-package

REMixed : Regularisation & Estimation for Mixed effects model