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