DESCRIPTION

Package: BDD
Type: Package
Title: Duplicate Detection Using a Bayesian Partitioning Approach
Version: 0.2.0
Date: 2021-01-24
Authors@R: c(
    person(given = "Neil", 
           family = "Marchant", 
           email = "ngmarchant@gmail.com", 
           role = c("aut", "cre")),
    person(given = "Rebecca",
           family = "Steorts", 
           email = "beka@stat.duke.edu",
           role = "aut"),
    person(given = "Benjamin",
           family = "Rubinstein", 
           email = "brubinstein@unimelb.edu.au", 
           role = "aut"))
Maintainer: Neil Marchant <ngmarchant@gmail.com>
URL: https://github.com/cleanzr/BDD
BugReports: https://github.com/cleanzr/BDD/issues
Description: An implementation of the Bayesian duplicate detection model 
    proposed by Sadinle (2014) <DOI:10.1214/14-AOAS779>. It resembles the 
    classic model of Fellegi & Sunter (1969) 
    <DOI:10.1080/01621459.1969.10501049>, but targets a partitioning of the 
    records, rather than pairwise match predictions. Inference is conducted 
    using a Gibbs sampler implemented in C++.
License: GPL (>= 2)
Depends: R (>= 3.0.2)
Imports: Rcpp (>= 0.12.12),
    coda (>= 0.17-1),
    methods,
    mcmcse (>= 1.4),
    progress (>= 1.2.2),
    fuzzyjoin (>= 0.1.6)
Suggests: knitr,
    rmarkdown,
    comparator (>= 0.1.1),
    magrittr (>= 1.5),
    clevr (>= 0.1.1)
LinkingTo: Rcpp, 
    RcppProgress, 
    BH (>= 1.69.0)
RoxygenNote: 7.1.1
Roxygen: list(markdown = TRUE)
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
Collate: 
    'BDD-package.R'
    'utils.R'
    'BDDModel.R'
    'BDDFit.R'
    'RcppExports.R'
    'data.R'
    'extract.R'
    'indexing.R'
    'run_inference.R'
    'scoring.R'