Fitting, simulation, and inference for antedependence models for
    longitudinal data, as described in Zimmerman and Nunez-Anton (2009,
    ISBN:9781420011074). Supports integer-valued antedependence (INAD) models
    for count data with thinning operators (binomial, Poisson, negative binomial)
    and flexible innovation distributions (Poisson, Bell, negative binomial),
    categorical antedependence models for discrete-state longitudinal outcomes,
    and Gaussian antedependence (AD) models for continuous data. Implements
    maximum likelihood estimation via time-separable optimization and block
    coordinate descent, with confidence intervals based on Louis' identity and
    profile likelihood.

Provides WHO Child Growth Standards (z-scores) with
             confidence intervals and standard errors around the
             prevalence estimates, taking into account complex sample designs.
             More information on the methods is
             available online:
             <https://www.who.int/tools/child-growth-standards>.

Provides WHO 2007 References for School-age Children and
             Adolescents (5 to 19 years) (z-scores) with
             confidence intervals and standard errors around the
             prevalence estimates, taking into account complex sample designs.
             More information on the methods is
             available online:
             <https://www.who.int/tools/growth-reference-data-for-5to19-years>.

Offers a graphical user interface for the calculation of the mean measure of divergence, with facilities for trait selection and graphical representations <doi:10.1002/ajpa.23336>.

Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed 		at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the 		statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.