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stratallo: Optimum Sample Allocation in Stratified Sampling

Provides exact analytical algorithms for computing optimum sample allocations in stratified sampling. Supports classical Neyman-Tschuprow allocation, minimum-cost allocation under a variance constraint, and multi-domain allocation with controlled precision. Handles lower and upper bounds, cost constraints, and multiple domains. Includes helper functions for variance computation, allocation summaries, rounding, and example datasets for testing and benchmarking.

Version: 3.0.1
Depends: R (≥ 3.5.0)
Imports: checkmate, lifecycle, Rdpack
Suggests: knitr, rmarkdown, spelling, testthat (≥ 3.0.0)
Published: 2026-03-12
DOI: 10.32614/CRAN.package.stratallo
Author: Wojciech Wójciak [aut, cre], Jacek Wesołowski [sad], Robert Wieczorkowski [ctb]
Maintainer: Wojciech Wójciak <wojciech.wojciak at gmail.com>
BugReports: https://github.com/wwojciech/stratallo/issues
License: GPL-2
Copyright: Wojciech Wójciak
URL: https://github.com/wwojciech/stratallo
NeedsCompilation: no
Language: en-US
Materials: README, NEWS
CRAN checks: stratallo results

Documentation:

Reference manual: stratallo.html , stratallo.pdf
Vignettes: Optimum Sample Allocation in Stratified Sampling with stratallo (source, R code)

Downloads:

Package source: stratallo_3.0.1.tar.gz
Windows binaries: r-devel: stratallo_2.2.1.zip, r-release: stratallo_2.2.1.zip, r-oldrel: stratallo_3.0.0.zip
macOS binaries: r-release (arm64): stratallo_3.0.1.tgz, r-oldrel (arm64): stratallo_3.0.1.tgz, r-release (x86_64): stratallo_3.0.1.tgz, r-oldrel (x86_64): stratallo_3.0.1.tgz
Old sources: stratallo archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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