Description
Sequential Poisson sampling is a variation of Poisson sampling for drawing probability-proportional-to-size samples with a given number of units, and is commonly used for price-index surveys. This package gives functions to draw stratified sequential Poisson samples according to the method by Ohlsson (1998, ISSN:0282-423X), as well as other order sample designs by Rosén (1997, <doi:10.1016/S0378-3758(96)00186-3>), and generate approximate bootstrap replicate weights according to the generalized bootstrap method by Beaumont and Patak (2012, <doi:10.1111/j.1751-5823.2011.00166.x>).
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CRAN Check Status
Show all 13 flavors
| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
Check History
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
Code
Structure
Lines of code
3,223
Files
40
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
11
Internal functions
21
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.93
testthat edition
3
CI present
No
CI type
[]
PR gated
No
Docs
Return-value doc rate
100%
\dontrun example ratio
0%
Roxygen coverage
100%
Has pkgdown
No
NEWS present
Yes
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.2
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
15
First release
2021-08-20
Latest release
2025-11-19
Avg cadence
84 days
Cold removal rate
–
Dep drift
2
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/cran-code-metrics.