Spbsampling: Spatially Balanced Sampling

Selection of spatially balanced samples. In particular, the implemented sampling designs allow to select probability samples well spread over the population of interest, in any dimension and using any distance function (e.g. Euclidean distance, Manhattan distance). For more details, Pantalone F, Benedetti R, and Piersimoni F (2022) <doi:10.18637/jss.v103.c02>, Benedetti R and Piersimoni F (2017) <doi:10.1002/bimj.201600194>, and Benedetti R and Piersimoni F (2017) <doi:10.48550/arXiv.1710.09116>. The implementation has been done in C++ through the use of 'Rcpp' and 'RcppArmadillo'.

Version: 1.3.5
Depends: R (≥ 3.1)
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
Published: 2022-08-24
DOI: 10.32614/CRAN.package.Spbsampling
Author: Francesco Pantalone [aut, cre], Roberto Benedetti [aut], Federica Piersimoni [aut]
Maintainer: Francesco Pantalone <pantalone.fra at gmail.com>
License: GPL-3
NeedsCompilation: yes
Citation: Spbsampling citation info
Materials: README NEWS
In views: Spatial
CRAN checks: Spbsampling results


Reference manual: Spbsampling.pdf


Package source: Spbsampling_1.3.5.tar.gz
Windows binaries: r-devel: Spbsampling_1.3.5.zip, r-release: Spbsampling_1.3.5.zip, r-oldrel: Spbsampling_1.3.5.zip
macOS binaries: r-release (arm64): Spbsampling_1.3.5.tgz, r-oldrel (arm64): Spbsampling_1.3.5.tgz, r-release (x86_64): Spbsampling_1.3.5.tgz, r-oldrel (x86_64): Spbsampling_1.3.5.tgz
Old sources: Spbsampling archive


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