BalancedSampling: Balanced and Spatially Balanced Sampling

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: 1.6.3
Imports: Rcpp (≥ 0.11.1), SamplingBigData
LinkingTo: Rcpp
Published: 2022-06-29
Author: Anton Grafström, Jonathan Lisic, Wilmer Prentius
Maintainer: Anton Grafström <anton.grafstrom at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: OfficialStatistics
CRAN checks: BalancedSampling results


Reference manual: BalancedSampling.pdf


Package source: BalancedSampling_1.6.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BalancedSampling_1.6.3.tgz, r-oldrel (arm64): BalancedSampling_1.6.3.tgz, r-release (x86_64): BalancedSampling_1.6.3.tgz, r-oldrel (x86_64): BalancedSampling_1.6.3.tgz
Old sources: BalancedSampling archive

Reverse dependencies:

Reverse imports: sgsR, SpotSampling
Reverse suggests: StratifiedSampling, WaveSampling


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