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:	2.1.1
Imports:	Rcpp (≥ 1.0.13)
LinkingTo:	Rcpp, RcppArmadillo
Published:	2024-11-18
DOI:	10.32614/CRAN.package.BalancedSampling
Author:	Anton Grafström [aut, cre], Wilmer Prentius [aut], Jonathan Lisic [ctb]
Maintainer:	Anton Grafström <anton.grafstrom at gmail.com>
License:	AGPL-3
URL:	https://www.envisim.se/, https://github.com/envisim/BalancedSampling/
NeedsCompilation:	yes
In views:	OfficialStatistics
CRAN checks:	BalancedSampling results

Documentation:

Reference manual:

BalancedSampling.pdf

Downloads:

Package source:	BalancedSampling_2.1.1.tar.gz
Windows binaries:	r-devel: BalancedSampling_2.1.1.zip, r-release: BalancedSampling_2.1.1.zip, r-oldrel: BalancedSampling_2.1.1.zip
macOS binaries:	r-release (arm64): BalancedSampling_2.1.1.tgz, r-oldrel (arm64): BalancedSampling_2.1.1.tgz, r-release (x86_64): BalancedSampling_2.1.1.tgz, r-oldrel (x86_64): BalancedSampling_2.1.1.tgz
Old sources:	BalancedSampling archive

Reverse dependencies:

Reverse imports:	sgsR
Reverse suggests:	WaveSampling

Linking:

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