EconPapers    
Economics at your fingertips  
 

Computing expectations and marginal likelihoods for permutations

Ben Powell () and Paul A. Smith ()
Additional contact information
Ben Powell: University of York
Paul A. Smith: University of Southampton

Computational Statistics, 2020, vol. 35, issue 2, No 20, 891 pages

Abstract: 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.

Keywords: Linkage error; Identity resolution; Object tracking; Random permutation; Matrix permanent (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00180-019-00901-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:35:y:2020:i:2:d:10.1007_s00180-019-00901-2

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-019-00901-2

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:compst:v:35:y:2020:i:2:d:10.1007_s00180-019-00901-2