Nonlinear Mixed Effects Models in Population PK/PD, Extra Support Functions
Stratified cross-validation fold generator function, inspired from the...
Create Horseshoe summary posterior estimates
Extract the equations from an nlmixr2/rxode2 model to produce a 'LaTeX...
Produce delta objective function for boostrap
Bootstrap nlmixr2 fit
Build covInfo list from varsVec and covarsVec
Build updated from the covariate and variable vector list
Control options for fixed-value likelihood profiling
Return Adaptive lasso coefficients after finding optimal t
Make dummy variable cols and updated covarsVec
Add covariate
Return Adjusted adaptive lasso coefficients after finding optimal t
Return Final lasso coefficients after finding optimal t
Create Lasso summary posterior estimates
Control options for log-likelihood profiling
Function to return data of normalized covariates
Sample from uniform distribution by optim
Linearly re-parameterize the model to be less sensitive to rounding er...
Perform likelihood profiling on nlmixr2 focei fits
Estimate the objective function values for a model while fixing define...
Profile confidence intervals with log-likelihood profiling
Give the output data.frame for a single model for profile.nlmixr2FitCo...
Objects exported from other packages
Regular lasso model
Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>). This package is for support functions like preconditioned fits <doi:10.1208/s12248-016-9866-5>, boostrap and stepwise covariate selection.
Useful links