Tools to build CDISC compliant data sets and check for CDISC
    compliance.

Diagnostics for non-linear mixed-effects (population) 
    models from 'NONMEM' <https://www.iconplc.com/solutions/technologies/nonmem/>. 
    'xpose' facilitates data import, creation of numerical run summary 
    and provide 'ggplot2'-based graphics for data exploration and model 
    diagnostics.

Extension to 'xpose' to support 'nlmixr2'. Provides functions to import 'nlmixr2' fit data into an 'xpose' data object, allowing the use of 'xpose' for 'nlmixr2' model diagnostics.

Adding some at-present missing functionality, or functions 
    unlikely to be added to the base 'xpose' package.  This includes some 
    diagnostic plots that have been missing in translation from 'xpose4', 
    but also some useful features that truly extend the capabilities of what 
    can be done with 'xpose'. These extensions include the concept of a set of
    'xpose' objects, and diagnostics for likelihood-based models.

A model building aid for nonlinear mixed-effects 
    (population) model analysis using NONMEM, facilitating data set 
    checkout, exploration and visualization, model diagnostics, candidate 
    covariate identification and model comparison. The methods are described 
    in Keizer et al. (2013) <doi:10.1038/psp.2013.24>, and Jonsson et al. (1999) 
    <doi:10.1016/s0169-2607(98)00067-4>.

There is limited native support for external pointers in the R interface.
 This package provides some basic tools to verify, create and modify 'externalptr' objects.

Support for interfaces from R to other languages,
    built around a class for evaluators and a combination of functions, classes and
    methods for communication. Will be used through a specific language interface
    package. Described in the book "Extending R".

Tools to analyze datasets previous to any statistical modeling.
    Has various functions designed to find inconsistencies and understanding the distribution of the data.

Fits flexible maximum likelihood regression models supporting censored,
    interval, and hybrid continuous/dichotomous data. Provides explicit analytic and
    numerical gradient computation, random intercept models via Gauss-Hermite
    quadrature, and multiple distribution families.