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-4.5-noble)BRISC_1.0.6.tar.gz(r-4.4-noble)
BRISC_1.0.6.tgz(r-4.4-emscripten)BRISC_1.0.6.tgz(r-4.3-emscripten)
BRISC.pdf |BRISC.html
BRISC/json (API)

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

Peer review:

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

2.80 score 2 packages 105 scripts 445 downloads 9 exports 6 dependencies

Last updated 24 days agofrom:f9734a6cbd. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 03 2024
R-4.5-linux-x86_64OKOct 03 2024

Exports:BRISC_bootstrapBRISC_correlationBRISC_decorrelationBRISC_estimationBRISC_neighborBRISC_orderBRISC_predictionBRISC_simulationBRISC_variogram.ci

Dependencies:matrixStatspbapplyRANNRcppRcppArmadillordist