Package: BalancedSampling 2.1.1

Anton Grafström

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>.

Authors:Anton Grafström [aut, cre], Wilmer Prentius [aut], Jonathan Lisic [ctb]

BalancedSampling_2.1.1.tar.gz
BalancedSampling_2.1.1.tar.gz(r-4.5-noble)BalancedSampling_2.1.1.tar.gz(r-4.4-noble)
BalancedSampling_2.1.1.tgz(r-4.4-emscripten)BalancedSampling_2.1.1.tgz(r-4.3-emscripten)
BalancedSampling.pdf |BalancedSampling.html
BalancedSampling/json (API)

# Install 'BalancedSampling' in R:
install.packages('BalancedSampling', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/envisim/balancedsampling/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

3.29 score 2 stars 1 packages 54 scripts 583 downloads 2 mentions 19 exports 2 dependencies

Last updated 23 days agofrom:e812751f53. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-linux-x86_64OKNov 19 2024

Exports:cubecubestratifiedgenpopPoissongenpopUniformgetPipshlpm2lcpslcubelcubestratifiedlpmlpm1lpm1slpm2rpmsbsblbscpsspmvsb

Dependencies:RcppRcppArmadillo