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Computing expectations and marginal likelihoods for permutations

Author

Listed:
  • Ben Powell

    (University of York)

  • Paul A. Smith

    (University of Southampton)

Abstract

This paper demonstrates how we can re-purpose sophisticated algorithms from a range of fields to help us compute expected permutations and marginal likelihoods. The results are of particular use in the fields of record linkage or identity resolution, where we are interested in finding pairs of records across data sets that refer to the same individual. All calculations discussed can be reproduced with the accompanying R package expperm.

Suggested Citation

  • Ben Powell & Paul A. Smith, 2020. "Computing expectations and marginal likelihoods for permutations," Computational Statistics, Springer, vol. 35(2), pages 871-891, June.
    • Handle: RePEc:spr:compst:v:35:y:2020:i:2:d:10.1007_s00180-019-00901-2
    DOI: 10.1007/s00180-019-00901-2
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    References listed on IDEAS

    as
    1. P. Lahiri & Michael D. Larsen, 2005. "Regression Analysis With Linked Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 222-230, March.
    2. Kim, Gunky & Chambers, Raymond, 2012. "Regression analysis under incomplete linkage," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2756-2770.
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