Publications & Presentations

Working Papers

“Scaling Bayesian Probabilistic Record Linkage with Post-Hoc Blocking: An Application to the California Great Registers”. McVeigh, B.; Spahn B; Murray, J. 2019. (arXiv)

“Practical Bayesian Inference for Record Linkage”. McVeigh, B.; Murray, J. 2017. (arXiv)

Presentations

“Practical Bayesian Record Linkage”. McVeigh, B.; Spahn, B.; Murray, J. Joint Statistical Meeting 2018, Vancouver, Canada. August 2018.

“Scalable Bayesian Record Linkage”. McVeigh, B.; Murray, J. NIPS Workshop, Advances in Approximate Bayesian Inference, Long Beach, California. December 2017. (paper, poster)

“A Sequential Algorithm for Bayesian Inference of Large-Scale Record Linkage Structure”. McVeigh, B.; Murray, J. Joint Statistical Meeting 2017, Baltimore, Maryland. July 2017.

Software

BayesianRecordLinkage

Julia implementation of unsupervised methods for one-to-one record linkage. Both an EM algorithm based method and a MCMC algorithm employing a standard Fellegi-Sunter based approach are included. The module also includes methods for post-hoc blocking and a penalized likelihood based point estimate that I have developed (here).

AssignmentSolver

Julia implementation of algorithms for solving linear sum assignment problems. This includes a version of the well known Hungarian algorithm as well as Auction algorithms (Bertsekas 1992).

ApproximateBayesianComputation

Julia implementation and the standard ABC rejection sampler as well as a Population Monte Carlo (PMC) sampler. Methods are also provided for more easily defining prior sampling distributions and adjusting the iterative process in the PMC sampler.

Teaching

Instructor

  • 36-201 Statistical Reasoning and Practice - Summer 2017

Teaching Assistant

  • 36-617 Applied Linear Models - Fall 2017
  • 36-494 Astrostatistics - Spring 2017
  • 36-315 Statistical Graphics and Visualization - Fall 2016
  • 36-226 Introduction to Statistical Inference - Spring 2016
  • 36-707 Regression Analysis - Fall 2015
  • 36-226 Introduction to Statistical Inference - Spring 2015
  • 36-401 Modern Regression - Fall 2014