Solving the disclosure auditing problem for secondary cell suppression by means of linear programming

Autor: de Waal, Ton, Coutinho, Wieger

Publikováno v: Transactions on Data Privacy, 13(2), 67-90. University of Skovde

National Statistical Institutes (NSIs) have the obligation to protect the privacy of individual persons or enterprises against disclosure of potentially sensitive information. For this reason, NSIs protect tabular data against disclosure of sensitive

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::9adadef922347075079d215d03b1887c
https://research.tilburguniversity.edu/en/publications/85bf93cd-956f-4094-836f-613cd9214747

Preserving logical relations while estimating missing values

Autor: de Waal, A.G., Coutinho, Wieger

Publikováno v: Romanian Statistical Review, 2017(3), 47-59. Romanian National Institute of Statistics

Item-nonresponse is often treated by means of an imputation technique. In some cases, the data have to satisfy certain constraints, which are frequently referred to as edits. An example of an edit for numerical data is that the profit of an enterpris

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https://research.tilburguniversity.edu/en/publications/c139f0c7-f5d4-4a22-a478-60159f38b39e

Imputation of numerical data under linear edit restrictions

Autor: Coutinho, Wieger, Ton de Waal, Remmerswaal, Marco

Publikováno v: SORT-Statistics and Operations Research Transactions; 2011: Vol.: 35 Núm.: 1 January-June; p. 39-62
oai:raco.cat:article/242562
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A common problem faced by statistical offices is that data may be missing from collected data sets. The typical way to overcome this problem is to impute the missing data. The problem of imputing missing data is complicated by the fact that statistic

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6a742ea948202c4189ae861850c379dd
https://hdl.handle.net/2099/11409

Automatic Editing for Business Surveys: An Assessment of Selected Algorithms.

Autor: Waal, Ton, Coutinho, Wieger

Publikováno v: International Statistical Review; Apr2005, Vol. 73 Issue 1, p73-102, 30p