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:
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')) |
Bug tracker:https://github.com/cleanzr/blink/issues
- RLdata500 - RLdata500
- identity.RLdata500 - Identity.RLdata500
Last updated 11 months agofrom:7aae7e9dbb. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-win | NOTE | Nov 05 2024 |
| R-4.5-linux | NOTE | Nov 05 2024 |
| R-4.4-win | NOTE | Nov 05 2024 |
| R-4.4-mac | NOTE | Nov 05 2024 |
| R-4.3-win | OK | Nov 05 2024 |
| R-4.3-mac | OK | Nov 05 2024 |
Exports:check_IDslinkslinks.comparemmsmpmmspairwiserl.gibbs
Dependencies:plyrRcppstringdist
