Package: BRISC 1.0.6

Arkajyoti Saha

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>.

Authors:Arkajyoti Saha [aut, cre], Abhirup Datta [aut], Jorge Nocedal [ctb], Naoaki Okazaki [ctb], Lukas M. Weber [ctb]

BRISC_1.0.6.tar.gz
BRISC_1.0.6.zip(r-4.7-x86_64)BRISC_1.0.6.zip(r-4.7-arm64)BRISC_1.0.6.zip(r-4.6-x86_64)BRISC_1.0.6.zip(r-4.6-arm64)
BRISC_1.0.6.tar.gz(r-4.7-arm64)BRISC_1.0.6.tar.gz(r-4.7-x86_64)BRISC_1.0.6.tar.gz(r-4.6-arm64)BRISC_1.0.6.tar.gz(r-4.6-x86_64)
BRISC_1.0.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
BRISC/json (API)

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

Bug tracker:https://github.com/arkajyotisaha/brisc/issues

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

On CRAN:

Conda:

openblascppopenmp

2.81 score 3 packages 71 scripts 727 downloads 9 exports 6 dependencies

Last updated from:f9734a6cbd. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK81
linux-devel-x86_64OK134
source / vignettesOK207
linux-release-arm64OK84
linux-release-x86_64OK109
windows-devel-arm64OK214
windows-devel-x86_64OK129
windows-release-arm64OK202
windows-release-x86_64OK91
wasm-releaseOK107

Exports:BRISC_bootstrapBRISC_correlationBRISC_decorrelationBRISC_estimationBRISC_neighborBRISC_orderBRISC_predictionBRISC_simulationBRISC_variogram.ci

Dependencies:matrixStatspbapplyRANNRcppRcppArmadillordist