Survey Sampling Algorithms
Overview
Fast implementations of survey sampling algorithms for single-stage probability sampling from finite populations, written in C. Provides equal probability methods (simple random sampling, systematic, Bernoulli), unequal probability methods (conditional Poisson / maximum entropy, Sampford, Brewer, systematic PPS, Pareto, sequential Poisson, Poisson, Chromy's minimum replacement, multinomial), balanced sampling via the cube method, and spatially balanced sampling via the local pivotal method and spatially correlated Poisson sampling. All sampling functions return design objects carrying sample indices, inclusion probabilities, and design metadata. Generics compute joint inclusion probabilities, pairwise expectations, and sampling covariances for variance estimation. Mostly based on algorithms from Tillé (2006, doi:10.1007/0-387-34240-0).
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Ahmadou Dicko <mail@ahmadoudicko.com>’ The BugReports field in DESCRIPTION has https://gitlab.com/dickoa/sondage/-/work_items which should likely be https://gitlab.com/dickoa/sondage/-/issues instead.
- NOTE11 OK, 2 NOTENow
- NOTE9 OK, 1 NOTE2026-08-05
- OK8 OK2026-08-04
Documentation
- Help pages
- 20includes a package overview page
- Examples that run
- 100%17 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 35%
Downloads
Repository
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Dependencies
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Code & Tests
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- 0.9.1Latest
- 0.9.02026-08-03
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-08-03
- Total releases
- 2 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.1.0
- Download size
- 207 KB
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