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 (2017) ''Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records'', available at <>.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.2.0 by Ted Enamorado, 19 days ago

Report a bug at

Browse source code at

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

Documentation:   PDF Manual  

GPL (>= 3) license

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

Linking to RcppArmadillo, Rcpp, RcppEigen

See at CRAN