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-4.4-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'))

Peer review:

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

Datasets:

On CRAN:

7 exports 5 stars 1.47 score 3 dependencies 1 dependents 61 scripts 292 downloads

Last updated 8 months agofrom:7aae7e9dbb. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 06 2024
R-4.5-winNOTESep 06 2024
R-4.5-linuxNOTESep 06 2024
R-4.4-winNOTESep 06 2024
R-4.4-macNOTESep 06 2024
R-4.3-winOKSep 06 2024
R-4.3-macOKSep 06 2024

Exports:check_IDslinkslinks.comparemmsmpmmspairwiserl.gibbs

Dependencies:plyrRcppstringdist

Introduction to blink

Rendered fromintroEBLink.Rmdusingknitr::rmarkdownon Sep 06 2024.

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