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.

Version: 1.0.0
Depends: R (≥ 3.0.2)
Imports: Rcpp, nloptr (≥ 1.2.0)
LinkingTo: Rcpp, RcppEigen, nloptr (≥ 1.2.0)
Published: 2024-09-20
DOI: 10.32614/CRAN.package.twingp
Author: Akhil Vakayil ORCID iD [aut, cre], V. Roshan Joseph ORCID iD [aut, ths], Jose L. Blanco [ctb] (nanoflann author)
Maintainer: Akhil Vakayil <akhilv at gatech.edu>
License: Apache License (== 2.0)
Copyright: See the file COPYRIGHTS for copyright details
twingp copyright details
NeedsCompilation: yes
CRAN checks: twingp results

Documentation:

Reference manual: twingp.pdf

Downloads:

Package source: twingp_1.0.0.tar.gz
Windows binaries: r-devel: twingp_1.0.0.zip, r-release: twingp_1.0.0.zip, r-oldrel: twingp_1.0.0.zip
macOS binaries: r-release (arm64): twingp_1.0.0.tgz, r-oldrel (arm64): twingp_1.0.0.tgz, r-release (x86_64): twingp_1.0.0.tgz, r-oldrel (x86_64): twingp_1.0.0.tgz

Linking:

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