Description: Provides data used by package 'dgo' in examples and vignettes.

Author: Taylor B. Arnold, John W. Emerson, R Core Team and contributors
Maintainer: Taylor B. Arnold <taylor.arnold@yale.edu>
Description: This package contains a proposed revision to the
stats::ks.test() function and the associated ks.test.Rd help
page.  With one minor exception, it does not change the
existing behavior of ks.test(), and it adds features necessary
for doing one-sample tests with hypothesized discrete
distributions.  The package also contains cvm.test(), for doing
one-sample Cramer-von Mises goodness-of-fit tests.

Maintainer: Taylor B. Arnold <taylor.b.arnold@gmail.com>

Description: A revision to the stats::ks.test() function and the associated
ks.test.Rd help page. With one minor exception, it does not change the
distributions. The package also contains cvm.test(), for doing

Title: Interface to 'dgpsi' for Deep and Linked Gaussian Process
person('Deyu', 'Ming', role = c('aut', 'cre', 'cph'),
person('Daniel', 'Williamson', role = c('aut'),
Description: Interface to the 'python' package 'dgpsi' for Gaussian process, deep Gaussian process,
and linked Gaussian process emulations of computer models and systems of computer
models. The implementations follow Ming & Guillas (2021) <doi:10.1137/20M1323771> and
Ming, Williamson, & Guillas (2022) <arXiv:2107.01590>. To get started with the package,
Imports: reticulate (>= 1.26), benchmarkme (>= 1.0.8), utils, ggplot2,
Suggests: knitr, rmarkdown, MASS, R.utils, spelling

Title: The Gumbel Distribution Functions and Gradients
person("Robin","Hogan",role="ctb", comment = "Author of included Adept library"),
person("The University of Reading", role=c("cph"), comment = "Copyright holder of included Adept library"))
Description: Gumbel distribution functions (De Haan L. (2007)
<doi:10.1007/0-387-34471-3>) implemented with the techniques of automatic
With this tool, a user should be able to quickly model extreme
events for which the Gumbel distribution is the domain of attraction.
The package makes available the density function, the distribution
function the quantile function and a random generating function. In
addition, it supports gradient functions. The package combines 'Adept'
(C++ templated automatic differentiation) (Hogan R. (2017)
<doi:10.5281/zenodo.1004730>) and 'Eigen' (templated matrix-vector
library) for fast computations of both objective functions and exact
gradients. It relies on 'RcppEigen' for easy access to 'Eigen' and
Author: Berent Ånund Strømnes Lunde [aut, cre, cph],
Robin Hogan [ctb] (Author of included Adept library),
The University of Reading [cph] (Copyright holder of included Adept