Package: variosig 0.3-1

Craig Wang

variosig: Testing Spatial Dependence Using Empirical Variogram

Applying Monte Carlo permutation to generate pointwise variogram envelope and checking for spatial dependence at different scales using permutation test. Empirical Brown's method and Fisher's method are used to compute overall p-value for hypothesis test.

Authors:Craig Wang [aut, cre], Reinhard Furrer [ctb]

variosig_0.3-1.tar.gz
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variosig_0.3-1.tgz(r-4.4-emscripten)variosig_0.3-1.tgz(r-4.3-emscripten)
variosig.pdf |variosig.html✨
variosig/json (API)
NEWS

# Install 'variosig' in R:
install.packages('variosig', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 140 downloads 3 exports 47 dependencies

Last updated 5 years agofrom:5d83aa4d8b. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 22 2025
R-4.5-linuxOKMar 22 2025
R-4.4-linuxOKMar 22 2025

Exports:envelopeenvplotenvsig

Dependencies:abindbriocallrclassclassIntclicrayonDBIdescdiffobjdigeste1071evaluateFNNfsgluegstatintervalsjsonliteKernSmoothlatticelifecyclemagrittrMASSpkgbuildpkgloadpraiseprocessxproxypsR6Rcpprlangrprojroots2sfsftimespspacetimestarstestthatunitswaldowithrwkxtszoo

Citation

To cite `variosig` in publication use:

Wang, C. and Furrer, R. (2018). Monte Carlo Permutation Tests for Assessing Spatial Dependence at Difference Scales, Nonparametric Statistics. (Submitted)

Corresponding BibTeX entry: 

  @Article{,
    title = {Monte Carlo Permutation Tests for Assessing Spatial
      Dependence at Difference Scales},
    author = {Craig Wang and Reinhard Furrer},
    journal = {Nonparametric Statistics},
    year = {2018},
  }