Fast Probabilistic Record Linkage with Missing Data

Implements a Fellegi-Sunter probabilistic record linkage model that allows for missing data and the inclusion of auxiliary information. This includes functionalities to conduct a merge of two datasets under the Fellegi-Sunter model using the Expectation-Maximization algorithm. In addition, tools for preparing, adjusting, and summarizing data merges are included. The package implements methods described in Enamorado, Fifield, and Imai (2019) ''Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records'', American Political Science Review and is available at <>.


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0.6.0 by Ted Enamorado, 2 years ago

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Authors: Ted Enamorado [aut, cre] , Ben Fifield [aut] , Kosuke Imai [aut]

Documentation:   PDF Manual  

Task views: Missing Data

GPL (>= 3) license

Imports Matrix, parallel, foreach, doParallel, gtools, data.table, stringdist, stringr, stringi, Rcpp, FactoClass, adagio, dplyr, plotrix, grDevices, graphics

Suggests testthat

Linking to RcppArmadillo, Rcpp, RcppEigen

See at CRAN