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 = 'https://cloud.r-project.org')

Bug tracker:https://github.com/arkajyotisaha/brisc/issues1 issues

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

On CRAN:

Conda:r-brisc-1.0.6(2025-03-25)

openblascppopenmp

1.78 score 2 packages 558 downloads 9 exports 6 dependencies

Last updated 6 months agofrom:f9734a6cbd. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-linux-x86_64OKApr 01 2025
R-4.4-linux-x86_64OKApr 01 2025

Exports:BRISC_bootstrapBRISC_correlationBRISC_decorrelationBRISC_estimationBRISC_neighborBRISC_orderBRISC_predictionBRISC_simulationBRISC_variogram.ci

Dependencies:matrixStatspbapplyRANNRcppRcppArmadillordist

Citation

To cite package ‘BRISC’ in publications use:

Saha A, Datta A (2024). BRISC: Fast Inference for Large Spatial Datasets using BRISC. R package version 1.0.6, https://CRAN.R-project.org/package=BRISC.

Corresponding BibTeX entry: 

  @Manual{,
    title = {BRISC: Fast Inference for Large Spatial Datasets using
      BRISC},
    author = {Arkajyoti Saha and Abhirup Datta},
    year = {2024},
    note = {R package version 1.0.6},
    url = {https://CRAN.R-project.org/package=BRISC},
  }