fastLink implements methods developed by Enamorado, Fifield, and Imai (2018)
''Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records'',
to probabilistically merge large datasets using the Fellegi-Sunter model
while allowing for missing data and the inclusion of auxiliary information.
The current version of this package conducts a merge of two datasets under
the Fellegi-Sunter model, using the Expectation-Maximization Algorithm. In addition,
tools for conducting and summarizing data merges are included.
Ted Enamorado ted.enamorado@gmail.com, Ben Fifield benfifield@gmail.com, and Kosuke Imai imai@harvard.edu
Maintainer: Ted Enamorado ted.enamorado@gmail.com
Enamorado, Ted, Ben Fifield and Kosuke Imai. (2019) "Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records." American Political Science Review. Vol. 113, No. 2. Available at https://imai.fas.harvard.edu/research/files/linkage.pdf.