Fast Probabilistic Record Linkage with Missing Data
Description
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 .