Reference

All functions
adaptivelassoCoefficients()	Return Adaptive lasso coefficients after finding optimal t
addCatCovariates()	Make dummy variable cols and updated covarsVec
addorremoveCovariate()	Add covariate
adjustedlassoCoefficients()	Return Adjusted adaptive lasso coefficients after finding optimal t
bootplot()	Produce delta objective function for boostrap
bootstrapFit()	Bootstrap nlmixr2 fit
buildcovInfo()	Build covInfo list from varsVec and covarsVec
buildupatedUI()	Build updated from the covariate and variable vector list
fixedControl()	Control options for fixed-value likelihood profiling
foldgen()	Stratified cross-validation fold generator function, inspired from the caret
horseshoeSummardf()	Create Horseshoe summary posterior estimates
knit_print(<nlmixr2FitCore>) knit_print(<rxUi>)	Extract the equations from an nlmixr2/rxode2 model to produce a 'LaTeX' equation.
lassoCoefficients()	Return Final lasso coefficients after finding optimal t
lassoSummardf()	Create Lasso summary posterior estimates
llpControl()	Control options for log-likelihood profiling
normalizedData()	Function to return data of normalized covariates
optimUnisampling()	Sample from uniform distribution by optim
preconditionFit()	Linearly re-parameterize the model to be less sensitive to rounding errors
profile(<nlmixr2FitCore>)	Perform likelihood profiling on nlmixr2 focei fits
profileFixed() profileFixedSingle()	Estimate the objective function values for a model while fixing defined parameter values
profileLlp()	Profile confidence intervals with log-likelihood profiling
profileNlmixr2FitCoreRet()	Give the output data.frame for a single model for profile.nlmixr2FitCore
regularmodel()	Regular lasso model
theoFitOde	Example single dose Theophylline ODE model