Package: SamplingBigData 1.0.0

SamplingBigData: Sampling Methods for Big Data

Select sampling methods for probability samples using large data sets. This includes spatially balanced sampling in multi-dimensional spaces with any prescribed inclusion probabilities. All implementations are written in C with efficient data structures such as k-d trees that easily scale to several million rows on a modern desktop computer.

Authors:Jonathan Lisic, Anton Grafström

SamplingBigData_1.0.0.tar.gz
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SamplingBigData.pdf |SamplingBigData.html✨
SamplingBigData/json (API)

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

Peer review:

Bug tracker:https://github.com/jlisic/samplingbigdata/issues

On CRAN:

4.48 score 10 stars 2 packages 8 scripts 267 downloads 2 exports 0 dependencies

Last updated 6 years agofrom:3b89b9152f. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-win-x86_64OKNov 01 2024
R-4.5-linux-x86_64OKNov 01 2024
R-4.4-win-x86_64OKNov 01 2024
R-4.4-mac-x86_64OKNov 01 2024
R-4.4-mac-aarch64OKNov 01 2024
R-4.3-win-x86_64OKNov 01 2024
R-4.3-mac-x86_64OKNov 01 2024
R-4.3-mac-aarch64OKNov 01 2024

Exports:lpm2_kdtreesplit_sample

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Sampling Methods for Big DataSamplingBigData-package SamplingBigData
Local Pivotal Methodlpm2_kdtree
Split Samplesplit_sample