Package: microclustr
Type: Package
Title: Entity Resolution with Random Partition Priors for
        Microclustering
Version: 0.1.0
Date: 2020-09-15
Authors@R: c(
    person(given=c("Rebecca", "C"), family="Steorts", role = c("aut","cre"), email="beka@stat.duke.edu"),
    person("Brenda", "Betancourt", email = "bbetancourt@ufl.edu", role = c("aut")),
    person("Giacomo", "Zanella", email = "zanella.gcm@gmail.com", role = c("aut"))
    )
Depends: R (>= 3.2.4)
Imports: Rcpp (>= 1.0.1), stats
Suggests: knitr, rmarkdown
Description: An implementation of the model in Betancourt, Zanella, Steorts (2020) <arXiv:2004.02008>, which performs microclustering models for categorical data. The package provides a vignette for two proposed methods in the paper as well as two standard Bayesian non-parametric clustering approaches for entity resolution. The experiments are reproducible and illustrated using a simple vignette. LICENSE: GPL-3 + file license. 
VignetteBuilder: knitr
License: GPL-3
LinkingTo: Rcpp
RoxygenNote: 7.1.1.9000
NeedsCompilation: yes
Packaged: 2020-09-28 15:10:13 UTC; rebeccasteorts
Author: Rebecca C Steorts [aut, cre],
  Brenda Betancourt [aut],
  Giacomo Zanella [aut]
Maintainer: Rebecca C Steorts <beka@stat.duke.edu>
Repository: CRAN
Date/Publication: 2020-10-01 08:30:02 UTC
