Optimal Imputation of Erroneous Data: Categorical Data, General Edits

R. S. Garfinkel, A. S. Kunnathur and G. E. Liepins
Additional contact information
R. S. Garfinkel: University of Tennessee, Knoxville, Tennessee
A. S. Kunnathur: University of Toledo, Toledo, Ohio
G. E. Liepins: Oak Ridge National Laboratory, Oak Ridge, Tennessee

Operations Research, 1986, vol. 34, issue 5, 744-751

Abstract: Responses to surveys often contain large amounts of incorrect information. One option for dealing with the problem is to revise those erroneous responses that can be detected. Fellegi and Holt developed a model in which a response is modified to pass a set of edits with as little change as possible. The model is called Minimum Weighted Fields to Impute (MWFI) and is NP-hard for categorical data and general edits. We develop two algorithms for MWFI, based on set covering, and present computational experience.

Keywords: 251 census data analysis; 630 set-covering algorithms; 797 correction of erroneous data (search for similar items in EconPapers)
Date: 1986
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.34.5.744 (application/pdf)

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:inm:oropre:v:34:y:1986:i:5:p:744-751

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().