Package: blink 1.1.0

Rebecca Steorts

blink: Record Linkage for Empirically Motivated Priors

An implementation of the model in Steorts (2015) <doi:10.1214/15-BA965SI>, which performs Bayesian entity resolution for categorical and text data, for any distance function defined by the user. In addition, the precision and recall are in the package to allow one to compare to any other comparable method such as logistic regression, Bayesian additive regression trees (BART), or random forests. The experiments are reproducible and illustrated using a simple vignette. LICENSE: GPL-3 + file license.

Authors:Rebecca Steorts [aut, cre]

blink_1.1.0.tar.gz
blink_1.1.0.zip(r-4.5)blink_1.1.0.zip(r-4.4)blink_1.1.0.zip(r-4.3)
blink_1.1.0.tgz(r-4.5-any)blink_1.1.0.tgz(r-4.4-any)blink_1.1.0.tgz(r-4.3-any)
blink_1.1.0.tar.gz(r-4.5-noble)blink_1.1.0.tar.gz(r-4.4-noble)
blink_1.1.0.tgz(r-4.4-emscripten)blink_1.1.0.tgz(r-4.3-emscripten)
blink.pdf |blink.html✨
blink/json (API)

# Install 'blink' in R:
install.packages('blink', repos = c('https://cleanzr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cleanzr/blink/issues

Datasets:

On CRAN:

5.72 score 5 stars 1 packages 70 scripts 283 downloads 7 exports 3 dependencies

Last updated 1 years agofrom:7aae7e9dbb. Checks:3 OK, 5 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 03 2025
R-4.5-winNOTEFeb 03 2025
R-4.5-macNOTEFeb 03 2025
R-4.5-linuxNOTEFeb 03 2025
R-4.4-winNOTEFeb 03 2025
R-4.4-macNOTEFeb 03 2025
R-4.3-winOKFeb 03 2025
R-4.3-macOKFeb 03 2025

Exports:check_IDslinkslinks.comparemmsmpmmspairwiserl.gibbs

Dependencies:plyrRcppstringdist

Introduction to blink

Rebecca C. Steorts

Rendered fromintroEBLink.Rmdusingknitr::rmarkdownon Feb 03 2025.

Last update: 2020-09-30
Started: 2017-06-20