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Computing expectations and marginal likelihoods for permutations

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Computing expectations and marginal likelihoods for permutations. / Powell, Benedict James; Smith, Paul.

In: Computational Statistics, 12.06.2019.

Research output: Contribution to journalArticlepeer-review

Harvard

Powell, BJ & Smith, P 2019, 'Computing expectations and marginal likelihoods for permutations', Computational Statistics. https://doi.org/10.1007/s00180-019-00901-2

APA

Powell, B. J., & Smith, P. (2019). Computing expectations and marginal likelihoods for permutations. Computational Statistics. https://doi.org/10.1007/s00180-019-00901-2

Vancouver

Powell BJ, Smith P. Computing expectations and marginal likelihoods for permutations. Computational Statistics. 2019 Jun 12. https://doi.org/10.1007/s00180-019-00901-2

Author

Powell, Benedict James ; Smith, Paul. / Computing expectations and marginal likelihoods for permutations. In: Computational Statistics. 2019.

Bibtex - Download

@article{45cd680aeb8a4886ada3550a74421af1,
title = "Computing expectations and marginal likelihoods for permutations",
abstract = "This paper demonstrates how we can re-purpose sophisticated algorithms from a range of fields to help us compute expected permutationsand marginal likelihoods. The results are of particular use in the fields ofrecord linkage or identity resolution, where we are interested in finding pairsof records across data sets that refer to the same individual. All calculationsdiscussed can be reproduced with the accompanying R package expperm.",
keywords = "Identity resolution, Linkage error, Matrix permanent, Object tracking, Random permutation",
author = "Powell, {Benedict James} and Paul Smith",
note = "{\textcopyright} The Author(s) 2019",
year = "2019",
month = jun,
day = "12",
doi = "10.1007/s00180-019-00901-2",
language = "English",
journal = "Computational Statistics",
issn = "0943-4062",
publisher = "Springer",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Computing expectations and marginal likelihoods for permutations

AU - Powell, Benedict James

AU - Smith, Paul

N1 - © The Author(s) 2019

PY - 2019/6/12

Y1 - 2019/6/12

N2 - This paper demonstrates how we can re-purpose sophisticated algorithms from a range of fields to help us compute expected permutationsand marginal likelihoods. The results are of particular use in the fields ofrecord linkage or identity resolution, where we are interested in finding pairsof records across data sets that refer to the same individual. All calculationsdiscussed can be reproduced with the accompanying R package expperm.

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

KW - Identity resolution

KW - Linkage error

KW - Matrix permanent

KW - Object tracking

KW - Random permutation

UR - http://www.scopus.com/inward/record.url?scp=85067417534&partnerID=8YFLogxK

U2 - 10.1007/s00180-019-00901-2

DO - 10.1007/s00180-019-00901-2

M3 - Article

JO - Computational Statistics

JF - Computational Statistics

SN - 0943-4062

ER -