The Greatest Mathematician Since Antiquity
Display a random fact about Carl Friedrich Gauss
based the on collection curated by Mike Cavers via the
<http://gaussfacts.com> site.

person(given = "Vikram B.",
family = "Baliga",
role = c("aut", "cre", "cph"),
email = "vbaliga87@gmail.com",
comment = c(ORCID = "0000-0002-9367-8974")
)
Functions to predict values from a two-dimensional Gaussian function and
produce plots of predicted data via either 'ggplot2' or base R plotting.
Vikram B. Baliga [aut, cre, cph]
(<https://orcid.org/0000-0002-9367-8974>)

Functions to fit two-dimensional Gaussian functions, predict values from
fits, and produce plots of predicted data via either 'ggplot2' or base R
plotting.

ggplot2 (>= 3.3.0), metR (>= 0.7.0), rgl, viridisLite

Bayesian Classification with High-dimensional Gaussian Profiles
This software is used to predict the discrete response
based on selected high dimensional features, such as gene
expression data. The data are modeled with Bayesian Gaussian
models. When a large number of features are available, one may
like to select only a subset of features to use, typically
those features strongly correlated with the response in
training cases. Such a feature selection procedure is however
invalid since the relationship between the response and the
features will appear stronger. This package provides a way to
avoid this bias and yields well-calibrated prediction for the
test cases when one uses F-statistic to select features.

Collection of functions for Gaussian quadrature
A collection of functions to perform Gaussian quadrature
with different weight functions corresponding to the orthogonal
polynomials in package orthopolynom.  Examples verify the
orthogonality and inner products of the polynomials.

Collection of Functions for Gaussian Quadrature

Multi-Trait Dissimilarity with more Uniform Contributions
c(person("Francesco", "de Bello", role = "aut",
email = "fradebel@ext.uv.es"),
person("Zoltan", "Botta-Dukat", role = "aut"),
person("Jan", "Leps", role = "aut"),
person("Pavel","Fibich", role = c("aut","cre"),
email = "pavel.fibich@prf.jcu.cz"))
Francesco de Bello [aut],
Zoltan Botta-Dukat [aut],
Jan Leps [aut],
Pavel Fibich [aut, cre]
R function gawdis() produces multi-trait dissimilarity with more uniform contributions of different traits. The approach is based on minimizing the differences in the correlation between the dissimilarity of each trait, or groups of traits, and the multi-trait dissimilarity. This is done using either an analytic or a numerical solution, both available in the function.