BRISC: Fast Inference for Large Spatial Datasets using BRISC

Fits bootstrap with univariate spatial regression models using Bootstrap for Rapid Inference on Spatial Covariances (BRISC) for large datasets using nearest neighbor Gaussian processes detailed in Saha and Datta (2018) <doi:10.1002/sta4.184>.

Version: 1.0.5
Depends: R (≥ 3.3.0), RANN, parallel, stats, rdist, matrixStats, pbapply, graphics
Published: 2022-04-29
Author: Arkajyoti Saha [aut, cre], Abhirup Datta [aut], Jorge Nocedal [ctb], Naoaki Okazaki [ctb], Lukas M. Weber [ctb]
Maintainer: Arkajyoti Saha <arkajyotisaha93 at gmail.com>
BugReports: https://github.com/ArkajyotiSaha/BRISC/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/ArkajyotiSaha/BRISC
NeedsCompilation: yes
CRAN checks: BRISC results

Documentation:

Reference manual: BRISC.pdf

Downloads:

Package source: BRISC_1.0.5.tar.gz
Windows binaries: r-devel: BRISC_1.0.5.zip, r-release: BRISC_1.0.5.zip, r-oldrel: BRISC_1.0.5.zip
macOS binaries: r-release (arm64): BRISC_1.0.5.tgz, r-oldrel (arm64): BRISC_1.0.5.tgz, r-release (x86_64): BRISC_1.0.5.tgz
Old sources: BRISC archive

Reverse dependencies:

Reverse imports: nnSVG, RandomForestsGLS

Linking:

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