Full metadata record
DC FieldValueLanguage
dc.contributor.authorFERRARI Pier Aldaen_GB
dc.contributor.authorANNONI Paolaen_GB
dc.contributor.authorBARBIERO Alessandroen_GB
dc.contributor.authorMANZI Giancarloen_GB
dc.date.accessioned2011-04-14T02:04:26Z-
dc.date.available2011-04-13en_GB
dc.date.available2011-04-14T02:04:26Z-
dc.date.created2011-03-14en_GB
dc.date.issued2011en_GB
dc.date.submitted2010-01-21en_GB
dc.identifier.citationCOMPUTATIONAL STATISTICS & DATA ANALYSIS vol. 55 no. 7 p. 2410-2420en_GB
dc.identifier.issn0167-9473en_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC56769-
dc.description.abstractThe problem of missing data in building multidimensional composite indicators is a delicate problem which is often underrated. An imputation method particularly suitable for categorical data is proposed. This method is discussed in detail in the framework of nonlinear principal component analysis and compared to other missing data treatments which are commonly used in this analysis. Its performance vs. these other methods is evaluated throughout a simulation procedure performed on both an artificial case, varying the experimental conditions, and a real case. The proposed procedure is implemented using R.en_GB
dc.description.sponsorshipJRC.DG.G.3-Econometrics and applied statisticsen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherELSEVIER SCIENCE BVen_GB
dc.relation.ispartofseriesJRC56769en_GB
dc.titleAn imputation method for categorical variables with application to nonlinear principal component analysisen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1016/j.csda.2011.02.007en_GB
JRC Directorate:Space, Security and Migration

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.