Package: WaveSampling 0.1.4

Raphaël Jauslin

WaveSampling: Weakly Associated Vectors (WAVE) Sampling

Spatial data are generally auto-correlated, meaning that if two units selected are close to each other, then it is likely that they share the same properties. For this reason, when sampling in the population it is often needed that the sample is well spread over space. A new method to draw a sample from a population with spatial coordinates is proposed. This method is called wave (Weakly Associated Vectors) sampling. It uses the less correlated vector to a spatial weights matrix to update the inclusion probabilities vector into a sample. For more details see Raphaël Jauslin and Yves Tillé (2019) <doi:10.1007/s13253-020-00407-1>.

Authors:Raphaël Jauslin [aut, cre], Yves Tillé [aut]

WaveSampling_0.1.4.tar.gz
WaveSampling_0.1.4.zip(r-4.7-x86_64)WaveSampling_0.1.4.zip(r-4.7-arm64)WaveSampling_0.1.4.zip(r-4.6-x86_64)WaveSampling_0.1.4.zip(r-4.6-arm64)
WaveSampling_0.1.4.tar.gz(r-4.7-arm64)WaveSampling_0.1.4.tar.gz(r-4.7-x86_64)WaveSampling_0.1.4.tar.gz(r-4.6-arm64)WaveSampling_0.1.4.tar.gz(r-4.6-x86_64)
WaveSampling_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
WaveSampling/json (API)

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

Bug tracker:https://github.com/rjauslin/wavesampling/issues

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

On CRAN:

Conda:

openblascpp

2.15 score 28 scripts 318 downloads 7 exports 4 dependencies

Last updated from:201df2f3ea. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK159
linux-devel-x86_64OK161
source / vignettesOK225
linux-release-arm64OK161
linux-release-x86_64OK161
windows-devel-arm64OK221
windows-devel-x86_64OK204
windows-release-arm64OK243
windows-release-x86_64OK205
wasm-releaseOK100

Exports:distUnitkIBsb_vkvarHAJwavewpikwpikInv

Dependencies:latticeMatrixRcppRcppArmadillo