Package: twingp 1.0.0

Akhil Vakayil

twingp: A Fast Global-Local Gaussian Process Approximation

A global-local approximation framework for large-scale Gaussian process modeling. Please see Vakayil and Joseph (2024) <doi:10.1080/00401706.2023.2296451> for details. This work is supported by U.S. NSF grants CMMI-1921646 and DMREF-1921873.

Authors:Akhil Vakayil [aut, cre], V. Roshan Joseph [aut, ths], Jose L. Blanco [ctb]

twingp_1.0.0.tar.gz
twingp_1.0.0.tar.gz(r-4.5-noble)twingp_1.0.0.tar.gz(r-4.4-noble)
twingp_1.0.0.tgz(r-4.4-emscripten)twingp_1.0.0.tgz(r-4.3-emscripten)
twingp.pdf |twingp.html✨
twingp/json (API)

# Install 'twingp' in R:
install.packages('twingp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 456 downloads 1 exports 3 dependencies

Last updated 3 months agofrom:521b7aa80c. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linux-x86_64OKNov 20 2024

Exports:twingp

Dependencies:nloptrRcppRcppEigen