R package fastLink: 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 <http://imai.princeton.edu/research/linkage.html>.
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References in zbMATH (referenced in 2 articles )
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- Slawski, Martin; Diao, Guoqing; Ben-David, Emanuel: A pseudo-likelihood approach to linear regression with partially shuffled data (2021)
- Slawski, Martin; Ben-David, Emanuel: Linear regression with sparsely permuted data (2019)