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BayesSampling

1.1.0Package record

Bayes Linear Estimators for Finite Population

0packages depend
3.2Kdownloads / year
–test coverage
11/13flavors OK

Overview

About

Allows the user to apply the Bayes Linear approach to finite population with the Simple Random Sampling - BLE_SRS() - and the Stratified Simple Random Sampling design - BLE_SSRS() - (both without replacement), to the Ratio estimator (using auxiliary information) - BLE_Ratio() - and to categorical data - BLE_Categorical(). The Bayes linear estimation approach is applied to a general linear regression model for finite population prediction in BLE_Reg() and it is also possible to achieve the design based estimators using vague prior distributions. Based on Gonçalves, K.C.M, Moura, F.A.S and Migon, H.S.(2014) https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X201400111886.

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespaces in Imports field not imported from:
  ‘MASS’ ‘Matrix’ ‘matrixcalc’ ‘stats’
All declared Imports should be used.

CRAN check page ↗

Slowest check: 2.1 min · r-release-macos-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.1.0
READMEYes · 1,266 wordsVignettesYes · 6 · dynamicNEWSNoCitation fileNoWebsiteYes
Help pages
14
Examples that run
100%5 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
43%

Downloads

3.2K
CRAN downloads in the past year
Rank #14,062 · ~9/day · ~267/mo
Daily download trend is not available in this view yet.
29030 days
84890 days
3.2K1 year
Compare downloads with other packages →
Also on92 r2u27 autocran

Repository

1Stars
0Forks
0Open issues
0Open PRs
0Releases
64Commits
1Commit identities
rpackagebayesiansamplingestimator
64 commits · Last activity 2021-05-01
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
not measured
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2020-05-17 · 12026-07-07 · 1
PracticesBeta

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

Checks run against github.com/pedrosfig/bayessampling on 2026-10-25.

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

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)

Installing BayesSampling adds 1 package (0 with compiled code, 30 KB of source tarballs). Heaviest: matrixcalc 30 KB.

Depends (1)
R >= 3.5
Imports (4)
MASSMatrixstatsmatrixcalc
LinkingTo (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 (2020)
Author, Thesis advisor
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 1.1.0Latest
    record
    2021-05-01 · current release · diff ↗ ·
    added 1 export
    BLE_Categorical
  • 1.0.0
    record
    2020-04-24
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26

Package metadata

First published
2020-04-24
Total releases
2 / 6 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5
Bundled data
611 KB / 1 file
Download size
656 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("BayesSampling")
Soares Figueiredo, P., & M. Gonçalves, K. C. (2021). BayesSampling: Bayes Linear Estimators for Finite Population (Version 1.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.BayesSampling

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 BayesSampling version 1.1.0 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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