Tool for Environment-Wide Association Studies (EnvWAS / EWAS) 
    which are repeated analysis. It includes three functions. One function for
    linear regression, a second for logistic regression and a last one for
    generalized linear models.

Correlation chart of two set (x and y) of data.  
  Using Quantiles.  Visualize the effect of factor.

Contains various routines for drawing
    ellipses and ellipse-like confidence regions, implementing the plots
    described in Murdoch and Chow (1996, <doi:10.2307/2684435>). There are
    also routines implementing the profile plots described in Bates and
    Watts (1988, <doi:10.1002/9780470316757>).

The ellipsis is a powerful tool for extending functions. Unfortunately 
    this power comes at a cost: misspelled arguments will be silently ignored. 
    The ellipsis package provides a collection of functions to catch problems
    and alert the user.

Provides functions for the simulation and
  the nonparametric estimation of elliptical distributions,
  meta-elliptical copulas and trans-elliptical distributions,
  following the article Derumigny and Fermanian (2022) <doi:10.1016/j.jmva.2022.104962>.

A suite of elliptic and related functions including Weierstrass and
 Jacobi forms.  Also includes various tools for manipulating and
 visualizing complex functions.

Given the omnipresence of the assumption of elliptical symmetry, it is essential to be able to test whether that assumption actually holds true or not for the data
            at hand. This package provides several statistical tests for elliptical symmetry that are described in Babic et al. (2021) <arXiv:2011.12560v2>.

Training and predict functions for Single Hidden-layer Feedforward Neural Networks (SLFN) using the Extreme Learning Machine (ELM) algorithm. The ELM algorithm differs from the traditional gradient-based algorithms for very short training times (it doesn't need any iterative tuning, this makes learning time very fast) and there is no need to set any other parameters like learning rate, momentum, epochs, etc. This is a reimplementation of the 'elmNN' package using 'RcppArmadillo' after the 'elmNN' package was archived. For more information, see "Extreme learning machine: Theory and applications" by Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew (2006), Elsevier B.V, <doi:10.1016/j.neucom.2005.12.126>.