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Select balanced and spatially balanced probability samples in multi-dimensional spaces with any prescribed inclusion probabilities. It contains fast (C++ via Rcpp) implementations of the included sampling methods. The local pivotal method by Grafström, Lundström and Schelin (2012) <doi:10.1111/j.1541-0420.2011.01699.x> and spatially correlated Poisson sampling by Grafström (2012) <doi:10.1016/j.jspi.2011.07.003> are included. Also the cube method (for balanced sampling) and the local cube method (for doubly balanced sampling) are included, see Grafström and Tillé (2013) <doi:10.1002/env.2194>.
Version: | 2.0.6 |
Imports: | Rcpp (≥ 1.0.12) |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2024-03-01 |
DOI: | 10.32614/CRAN.package.BalancedSampling |
Author: | Anton Grafström, Jonathan Lisic, Wilmer Prentius |
Maintainer: | Anton Grafström <anton.grafstrom at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://www.envisim.se/, https://github.com/envisim/BalancedSampling/ |
NeedsCompilation: | yes |
In views: | OfficialStatistics |
CRAN checks: | BalancedSampling results |
Reference manual: | BalancedSampling.pdf |
Package source: | BalancedSampling_2.0.6.tar.gz |
Windows binaries: | r-devel: BalancedSampling_2.0.6.zip, r-release: BalancedSampling_2.0.6.zip, r-oldrel: BalancedSampling_2.0.6.zip |
macOS binaries: | r-release (arm64): BalancedSampling_2.0.6.tgz, r-oldrel (arm64): BalancedSampling_2.0.6.tgz, r-release (x86_64): BalancedSampling_2.0.6.tgz, r-oldrel (x86_64): BalancedSampling_2.0.6.tgz |
Old sources: | BalancedSampling archive |
Reverse imports: | sgsR |
Reverse suggests: | WaveSampling |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.