Tool to find where a function has its lowest value(minimum). The
functions can be any dimensions. Recommended use is with eps=10^-10, but can be
run with 10^-20, although this depends on the function. Two more methods are in
this package, simple gradient method (Gradmod) and Powell method (Powell). These
are not recommended for use, their purpose are purely for comparison.

Species Identification using DNA Barcodes
c(person("Ai-bing", "ZHANG",  role = c("aut", "cre"),email = "Zhangab2008@mail.cnu.edu.cn"),person("Meng-di", "HAO",  role = c("aut"),email = "dreamdy521@163.com"),person("Cai-qing", "YANG",  role = c("aut"),email = "279226090@qq.com"),person("Zhi-yong", "SHI",  role = c("aut"),email = "zhiyong-shi@163.com"))
To perform species identification using DNA barcodes.
Ai-bing ZHANG [aut, cre],
Meng-di HAO [aut],
Cai-qing YANG [aut],
Zhi-yong SHI [aut]

Barnard's unconditional test for 2x2 contingency tables.

Variable Selection Using Bayesian Additive Regression Trees
c(person('Chuji', 'Luo', role=c('aut', 'cre'),
email='cjluo@ufl.edu'),
person('Michael J.', 'Daniels', role='aut'),
person('Robert', 'McCulloch', role='ctb'),
person('Rodney', 'Sparapani', role='ctb'))
Chuji Luo [aut, cre],
Michael J. Daniels [aut],
Robert McCulloch [ctb],
Rodney Sparapani [ctb]
Bayesian additive regression trees (BART) provides flexible non-parametric modeling of mixed-type predictors for continuous and binary responses. This package is built upon CRAN R package 'BART', version 2.7 (<https://github.com/cran/BART>). It implements the three proposed variable selection approaches in the paper: Luo, C and Daniels, M. J. (2021), "Variable Selection Using Bayesian Additive Regression Trees." <arXiv:2112.13998>, and other three existing BART-based variable selection approaches.

Computation of a Wasserstein Barycenter. The package implements a method described in Cuturi (2014) "Fast Computation of Wasserstein Barycenters". The paper is available at <http://jmlr.org/proceedings/papers/v32/cuturi14.pdf>. To speed up the computation time the main iteration step is based on 'RcppArmadillo'.