Represents generalized geometric ellipsoids with the "(U,D)" representation. It allows degenerate
	and/or unbounded ellipsoids, together with methods for linear and duality transformations, and for plotting.
	Thus ellipsoids are naturally extended to include lines, hyperplanes, points, cylinders, etc.
	This permits exploration of a variety to statistical issues that can be visualized using ellipsoids
	as discussed by Friendly, Fox & Monette (2013), Elliptical Insights: Understanding Statistical Methods 
	Through Elliptical Geometry <doi:10.1214/12-STS402>.

Implements several extensions of the elastic net regularization
    scheme. These extensions include individual feature penalties for the L1 term,
    feature-feature penalties for the L2 term, as well as translation coefficients
    for the latter.

Provides functions to calculate the best linear unbiased prediction of genotype-by-environment metrics: ecovalence, environmental variance, Finlay and Wilkinson regression and Lin and Binns superiority measure, based on a multi-environment genomic prediction model.

Provides a comprehensive interface for Google Gemini API, 
            enabling users to access and utilize Gemini Large Language Model (LLM) functionalities directly from R. 
            This package facilitates seamless integration with Google Gemini, allowing for advanced language processing, 
            text generation, and other AI-driven capabilities within the R environment.
            For more information, please visit <https://ai.google.dev/docs/gemini_api_overview>.

Fits a multivariate linear mixed effects model that uses a polygenic term, after Zhou & Stephens (2014) (<https://www.nature.com/articles/nmeth.2848>). Of particular interest is the estimation of variance components with restricted maximum likelihood (REML) methods. Genome-wide efficient mixed-model association (GEMMA), as implemented in the package 'gemma2', uses an expectation-maximization algorithm for variance components inference for use in quantitative trait locus studies.