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Workflow-Oriented Survey Weight Calibration

0packages depend
706downloads / year
80.0%test coverage
13/13flavors OK

Overview

About
Maintained by Kunxiang MaCRAN page ↗GitHub ↗Issues ↗Declared funder: WEIAN DATA TECH (Beijing) Co., Ltd.

Provides a disciplined precheck, execution, and diagnostics workflow for survey weighting and raking. Weight construction requires design-only data, a verified external target, outcome-blind planning, and human approval before weight locking, with bilingual reports for decision and statistical audiences. Converts calibrated and replicate weights into standard survey designs, provides optional broom-style result projections, and records serializable production pipeline provenance. Supports fixed, predeclared soft calibration tolerances and categorical entropy balancing from verified margins, plus panel attrition weighting, high-influence unit diagnostics, Fay's balanced repeated replication, and opt-in parallel execution for long runs. Calibration methods follow Deville and Saerndal (1992) doi:10.1080/01621459.1992.10475217, and entropy balancing follows Hainmueller (2012) doi:10.1093/pan/mpr025.

Changes in 2.0.1

Documentation-only release prepared in response to the CRAN pre-acceptance

review of 2.0.0. No user-visible behavior changed.

  • wf_report() now carries a self-contained, executable example built on wf_attrition() weights, replacing the previous \dontrun{} block.
  • The non-installed prototype in inst/reference/wfc_future_usability.R restores graphics::par() with the explicit oldpar idiom instead of on.exit(), matching the CRAN convention for script files.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.7 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK7 OK2026-08-07
Advisories

none known

Documentation

In release 2.0.1
READMEYes · 671 wordsVignettesYes · 10 · dynamicNEWSYes · 100% structured · mentions 2.0.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
72
Examples that run
100%10 run in a plain check
Exported functions with examples
24%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

706
CRAN downloads in the past year
Rank #18,007 · ~2/day · ~59/mo
Daily download trend is not available in this view yet.
31930 days
70690 days
7061 year
Compare downloads with other packages →
Also on14 r2u2 autocran

Repository

0Stars
0Forks
0Open issues
0Open PRs
2Releases
51Commits
2Commit identities
License file reads as GPL-2.0 · 51 commits · Last activity 2026-07-31
Responsiveness
How these are sampled
PRs merged (all time)
92%
Median days to close, 50 most recently updated closed issues
6
Median days to close, 50 most recently updated closed PRs
0
PracticesBeta

14 development-tooling and community-health practices detected across 8 families in the upstream repository

Checks run against github.com/weiandata/wfc on 2026-10-11.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (6)
Code of conductContributing guideIssue templatesPR templateSecurity policyCODEOWNERS
Docs source (1)
pkgdown
Coverage (1)
Coverage reporting
Show all practicesHide 4 practices
Reproducibility and dev environment (1)
data-raw/
CRAN release process (1)
cran-comments.md
Lint, format, editor (1)
EditorConfig
Git structural (1)
.gitattributes
How this is detected·Detection ruleset v3 (2026-09-26)
AI coding toolsBeta

This repository shows signs of AI coding tools.

  • Claude Codefirst seen 2026-07-28
    Named in .Rbuildignore: .claude
    Commits: at least 1 crediting it in the message
Shared conventions any agent may read, so they name no particular tool.
Seen in the repository: AGENTS.md
From outside contributors
  • Claude Code
    Pull requests: 1 from outside contributors, first on 2026-07-28
Models named in its commits
  • Claude Opus 51 commit · Jul 2026
Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)

Installing WFC adds 1 package (1 with compiled code, 231 KB of source tarballs). Heaviest: digest 231 KB.

Depends (1)
R >= 3.6.0
Imports (4)
digestparallelstatsutils
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 2.0.1 (2026)
Copyright holder, Funder
Releases (1)
  • 2.0.1Latest
    2026-08-06 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-08-06
Total releases
1 / 1 yrs
License
GPL (>= 2) OSI
Copyright
See file inst/COPYRIGHTS.
Minimum R
≥ 3.6.0
Bundled data
0.5 KB / 1 file
Download size
270 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("WFC")
Ma, K., & WEIAN DATA TECH (Beijing) Co., Ltd. (2026). WFC: Workflow-Oriented Survey Weight Calibration (Version 2.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.WFC

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for WFC version 2.0.1 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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