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boiwsa

1.1.5Package record

Seasonal Adjustment of Weekly Data

0packages depend
4Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Perform seasonal adjustment and forecasting of weekly data. The package provides a user-friendly interface for computing seasonally adjusted estimates and forecasts of weekly time series and includes functions for the construction of country-specific prior adjustment variables, as well as diagnostic tools to assess the quality of the adjustments. The methodology is described in more detail in Ginker (2024) doi:10.13140/RG.2.2.12221.44000.

Changes in 1.1.5

Added plot_weekly_patterns() to visualize intra-monthly and intra-yearly patterns in weekly data using detrended boxplots. The function accepts separate date and observation vectors or a boiwsa object to inspect the seasonally adjusted series for remaining seasonal patterns. Added examples to the README.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 2.4 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.1.5
READMEYes · 2,110 wordsVignettesNoNEWSYes · 67% structured · mentions 1.1.5Citation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
Cites an R Journal article
Help pages
20
Examples that run
70%7 run in a plain check · 3 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
83%
Documented parameters
100%
Return-value docs
83%
Help pages citing references
10%

Downloads

4K
CRAN downloads in the past year
Rank #8,148 · ~11/day · ~332/mo
Daily download trend is not available in this view yet.
51730 days
1.1K90 days
4K1 year
Compare downloads with other packages →
Also on134 r2u34 autocran33 c2d4u

Repository

6Stars
2Forks
2Open issues
0Open PRs
2Releases
171Commits
2Commit identities
r-packageseasonal-adjustmentseasonalitytime-series-analysis
171 commits · Last activity 2026-09-26 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
1
Median days to close, 50 most recently updated closed PRs
4

Stars over time

2025-07-30 · 52026-07-07 · 6
PracticesBeta

4 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/timginker/boiwsa on 2026-10-22.

Docs source (1)
README.Rmd
CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)

Installing boiwsa adds 71 packages (41 with compiled code, 64 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (1)
R >= 2.10
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 1.0.0 (2023), Copyright holder
Contributor · added in 1.1.3
Releases (7)

Pick two releases to compare their code metrics.

  • 1.1.5Latest
    record
    2026-09-26 · current release · diff ↗ ·
    added 1 export
    plot_weekly_patterns
  • R
    R 4.6.0 released · 2026-04-24
  • 1.1.4
    record
    2025-12-14 · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 1.1.3
    record
    2025-02-05 · diff ↗
  • 1.1.2
    record
    2024-09-23 · diff ↗ ·
    added 2 exports
    print, summary
  • 1.1.1
    record
    2024-06-05 · diff ↗
  • 1.1.0
    record
    2024-05-22 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • 1.0.0
    record
    2023-10-12
  • R
    R 4.3.0 released · 2023-04-21

Package metadata

First published
2023-10-12
Total releases
7 / 3 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 2.10
Bundled data
95 KB / 4 files
Download size
190 KB
Appears in task views

Cite

Cite this package

Run in R for the authors' entry:

citation("boiwsa")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.32614/rj-2024-032.

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 boiwsa version 1.1.5 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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