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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
backwardSearch()
Backward covariate search
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
covarSearchAuto()
Stepwise Covariate Model-selection (SCM) method
foldgen()
Stratified cross-validation fold generator function, inspired from the caret
forwardSearch()
Forward covariate search
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
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
regularmodel()
Regular lasso model
theoFitOde
Example single dose Theophylline ODE model