Title: Balanced and Spatially Balanced Sampling for Big Data
Author: Jonathan Lisic, Anton Grafström
Maintainer: Jonathan Lisic jlisic@gmail.com
Description: 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.
License: GPL (>=2)
Encoding: UTF-8
URL: https://github.com/jlisic/SamplingBigData
NeedsCompilation: yes