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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 |
| 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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