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.

A model library for 'nlmixr2'.  The models include
  (and plan to include) pharmacokinetic, pharmacodynamic, and
  disease models used in pharmacometrics.  Where applicable,
  references for each model are included in the meta-data for
  each individual model.  The package also includes model
  composition and modification functions to make model updates
  easier.

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
    'ggplot2' plotting methods for 'nlmixr2' objects.

This allows you to generate reporting workflows around 'nlmixr2' analyses with outputs in Word and PowerPoint. You can specify figures, tables and report structure in a user-definable 'YAML' file. Also you can use the internal functions to access the figures and tables to allow their including in other outputs (e.g. R Markdown).

Provides functions to fit linear mixed models
	based on convolutions of the generalized Laplace (GL) distribution.
	The GL mixed-effects model includes four special cases with normal random
	effects and normal errors (NN), normal random effects and Laplace errors (NL),
	Laplace random effects and normal errors (LN), and Laplace random effects
	and Laplace errors (LL). The methods are described in Geraci and Farcomeni (2020,
	Statistical Methods in Medical Research) <doi:10.1177/0962280220903763>.