Package: rsamplr 0.2.0

rsamplr: Sampling Algorithms and Spatially Balanced Sampling

Fast tools for unequal probability sampling in multi-dimensional spaces, implemented in Rust for high performance. The package offers a wide range of methods, including Sampford (Sampford, 1967, <doi:10.1093/biomet/54.3-4.499>) and correlated Poisson sampling (Bondesson and Thorburn, 2008, <doi:10.1111/j.1467-9469.2008.00596.x>), pivotal sampling (Deville and Tillé, 1998, <doi:10.1093/biomet/91.4.893>), and balanced sampling such as the cube method (Deville and Tillé, 2004, <doi:10.1093/biomet/91.4.893>) to ensure auxiliary totals are respected. Spatially balanced approaches, including the local pivotal method (Grafström et al., 2012, <doi:10.1111/j.1541-0420.2011.01699.x>), spatially correlated Poisson sampling (Grafström, 2012, <doi:10.1016/j.jspi.2011.07.003>), and locally correlated Poisson sampling (Prentius, 2024, <doi:10.1002/env.2832>), provide efficient designs when the target variable is linked to auxiliary information.

Authors:Wilmer Prentius [aut, cre], Anton Grafström [ctb], Authors of the dependent Rust crates [aut]

rsamplr_0.2.0.tar.gz
rsamplr_0.2.0.zip(r-4.7-x86_64)rsamplr_0.2.0.zip(r-4.7-arm64)rsamplr_0.2.0.zip(r-4.6-x86_64)rsamplr_0.2.0.zip(r-4.6-arm64)rsamplr_0.2.0.zip(r-4.5-x86_64)
rsamplr_0.2.0.tgz(r-4.6-x86_64)rsamplr_0.2.0.tgz(r-4.6-arm64)rsamplr_0.2.0.tgz(r-4.5-x86_64)rsamplr_0.2.0.tgz(r-4.5-arm64)
rsamplr_0.2.0.tar.gz(r-4.7-arm64)rsamplr_0.2.0.tar.gz(r-4.7-x86_64)rsamplr_0.2.0.tar.gz(r-4.6-arm64)rsamplr_0.2.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rsamplr/json (API)

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

Bug tracker:https://github.com/envisim/rust-samplr/issues

On CRAN:

Conda:

rustcargo

1.00 score 1 scripts 220 downloads 37 exports 0 dependencies

Last updated from:774df4b8b3. Checks:14 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK92
linux-devel-x86_64OK106
source / vignettesOK210
linux-release-arm64OK89
linux-release-x86_64OK98
macos-release-arm64OK103
macos-release-x86_64OK284
macos-oldrel-arm64OK198
macos-oldrel-x86_64OK481
windows-devel-arm64OK350
windows-devel-x86_64OK143
windows-release-arm64OK376
windows-release-x86_64OK147
windows-oldrel-x86_64OK89
wasm-releaseFAIL104

Exports:balance_deviationbrewerconditional_poissoncpscubecube_stratifieddbd_circulardbd_circular_iterdbd_tcdbd_tc_iterdrawlcpslocal_cubelocal_cube_stratifiedlocal_mean_variancelpm_1lpm_1slpm_2lpm_2_hierarchicalparetopips_from_vectorpoissonrpmsampfordsample_to_indicatorscpsspatial_balance_allspatial_balance_all_equalspatial_balance_energyspatial_balance_energy_equalspatial_balance_localspatial_balance_local_equalspatial_balance_voronoispatial_balance_voronoi_equalspmsystematicsystematic_random_order

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Distributionally balanced designs defaults.dbd_defaults
Sampling defaults.sampling_defaults
Balanced samplingBalanced sampling cube cube_stratified
Distributionally balanced designsdbd_circular dbd_tc Distributionally balanced designs
Doubly balanced samplingDoubly balanced sampling local_cube local_cube_stratified
Draw from a sampling designdraw draw.dbd
Iterative evaluation of distributional designsdbd_circular_iter dbd_tc_iter Iterative evaluation of distributional designs
Variance estimator for spatially balanced sampleslocal_mean_variance
Inclusion probabilities proportional-to-sizepips_from_vector
Transform a sample vector into an inclusion indicator vectorsample_to_indicator
Spatial balance measurebalance_deviation Spatial balance measure spatial_balance_all spatial_balance_all_equal spatial_balance_energy spatial_balance_energy_equal spatial_balance_local spatial_balance_local_equal spatial_balance_voronoi spatial_balance_voronoi_equal
Spatially balanced samplinglcps lpm_1 lpm_1s lpm_2 lpm_2_hierarchical scps Spatially balanced sampling
Unequal probability samplingbrewer conditional_poisson cps pareto poisson rpm sampford spm systematic systematic_random_order Unequal probability sampling