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.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✨
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

2.69 score 2 packages 81 scripts 796 downloads 9 exports 6 dependencies

Last updated from:f9734a6cbd. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK110
linux-devel-x86_64OK111
source / vignettesOK190
linux-release-arm64OK105
linux-release-x86_64OK115
wasm-releaseOK101

Exports:BRISC_bootstrapBRISC_correlationBRISC_decorrelationBRISC_estimationBRISC_neighborBRISC_orderBRISC_predictionBRISC_simulationBRISC_variogram.ci

Dependencies:matrixStatspbapplyRANNRcppRcppArmadillordist