Uses simple Bayesian conjugate prior update rules to calculate 
    the win probability of each option, value remaining in the test, and 
    percent lift over the baseline for various marketing objectives.
    References: 
    Fink, Daniel (1997) "A Compendium of Conjugate Priors" <https://www.johndcook.com/CompendiumOfConjugatePriors.pdf>.
    Stucchio, Chris (2015) "Bayesian A/B Testing at VWO" <https://vwo.com/downloads/VWO_SmartStats_technical_whitepaper.pdf>.

Quantitative genetics tool supporting the modelling of multivariate 
 genetic variance structures in quantitative data. It allows fitting different 
 models through multivariate genetic-relationship-matrix (GRM) 
 structural equation modelling (SEM) in unrelated individuals, 
 using a maximum likelihood approach. Specifically, 
 it combines genome-wide genotyping information, as captured by GRMs, 
 with twin-research-based SEM techniques, 
 St Pourcain et al. (2017) <doi:10.1016/j.biopsych.2017.09.020>, 
 Shapland et al. (2020) <doi:10.1101/2020.08.14.251199>.

The program GRNN implements the algorithm proposed by
        Specht (1991).

This General Regression Neural Networks Package uses various distance functions.
     It was motivated by Specht (1991, ISBN:1045-9227), and updated from previous published paper 
     Li et al. (2016) <doi:10.1016/j.palaeo.2015.11.005>. This package includes various functions, 
     although "euclidean" distance is used traditionally.

Workbench for testing genomic regression accuracy on
    (optionally noisy) phenotypes.

A tool which allows users the ability to intuitively create 
  flexible, reproducible portable document format reports comprised of 
  aesthetically pleasing tables, images, plots and/or text.

Robust multiple or multivariate linear regression, nonparametric regression on orthogonal components, classical or robust partial least squares models as described in Bilodeau, Lafaye De Micheaux and Mahdi (2015) <doi:10.18637/jss.v065.i01>.

Computes Gromov-Hausdorff type l^p distances for labeled metric spaces. These distances were introduced in V.Liebscher, Gromov meets Phylogenetics - new Animals for the Zoo of Metrics on Tree Space <arXiv:1504.05795>  for phylogenetic trees, but may apply to a diversity of scenarios.