Objectif The project will evaluate and compare the current methods for editing and imputation to establish current best practice methods. In addition, new methods for editing and imputation based on neural networks, support vector machine, fuzzy logic methodology and robust statistical methods will be developed and compared with the current best practice methods. The evaluation of different methods will require, (a) the creation of common data sets with known type of errors to be used by all the methods, and (b) the establishment of sound statistical criteria for the objective evaluation of the methods. Based on our evaluation, recommendations for the use of different methods for editing and imputation for different kinds of data sets will be made. A CD ROM containing the algorithms for different selected methods will be produced and widely disseminated for use by the NSIs and other private and public sector organisations interested in editing and imputation.Objectives:1. To establish a standard collection of data sets for EUREDIT2. To develop a methodological evaluation framework and develop evaluation criteria3. To establish a baseline by evaluating currently used methods for data editing and imputation.4. To develop and evaluate a selected range of new techniques for data editing and imputation.5. To evaluate different methods for edit and imputation and establish best methods for different types of data.6. To disseminate the best methods via a single package for wider dissemination, and in a conference proceedings.Work description:In order to evaluate the editing and imputation methods, a set of representative data sets arising in social sciences (household surveys, business surveys, censuses, panel data) with known types of errors will be produced. The criteria for the evaluation of the methods in terms of Fellegi-Holt (1976) principles and operational efficiency will be established and agreed among the participants. Based on a review of currently used methods, a selection will be evaluated. This will establish the current best practice methods and also provide benchmark for the later phase of the project. Alongside the investigation of traditional methods, new methods for editing and imputation based upon advanced statistical and information technology techniques will be developed. Specifically, methods based upon: outlier robust methods and non-parametric regression, MLP neural networks, Radial Basis Function (RBF) neural networks, Correlation Matrix Memory (CMM) neural networks, Self-Organising Map (SOM) neural networks and Support Vector Machines (SVM), will be developed. This will involve the establishment of appropriate methodology, development of algorithms and application of methods to the selected data sets. All the methods (new and old) will be comparatively evaluated. This will form the basis for detailed recommendations about the optimal choice of methods in a wide range of common situations. The "best methods" will be selected for wider dissemination. This will be achieved through the development of portable software for the selected (best) methods. The CD containing the software will be produced and made available to the organisations interested in editing and imputation.Milestones:1. Selection and compilation of datasets for evaluating methods2. Determination objective quality criteria for evaluating methodsL%3. Development and testing of selected new methods for error localisation4. Development and testing of selected new methods for imputation5. Evaluation of all (new and old) editing and imputation methods6. Integration of the individual edit and imputation methods into a single Champ scientifique natural sciencescomputer and information sciencessoftwaresocial sciencessociologydemographycensusnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Programme(s) FP5-IST - Programme for research, technological development and demonstration on a "User-friendly information society, 1998-2002" Thème(s) 1.1.2.-5.1.4 - CPA4: New indicators and statistical methods Appel à propositions Data not available Régime de financement CSC - Cost-sharing contracts Coordinateur OFFICE OF NATIONAL STATISTICS Contribution de l’UE Aucune donnée Adresse 1, DRUMMOND GATE SW1V 2QQ LONDON Royaume-Uni Voir sur la carte Coût total Aucune donnée Participants (12) Trier par ordre alphabétique Trier par contribution de l’UE Tout développer Tout réduire CENTRAAL BUREAU VOOR DE STATISTIEK Pays-Bas Contribution de l’UE Aucune donnée Adresse PRINSES BEATRIXLAAN 428 2270 JM VOORBURG Voir sur la carte Coût total Aucune donnée CREDIT SUISSE FINANCIAL PLANNING SOLUTIONS GMBH Allemagne Contribution de l’UE Aucune donnée Adresse WILHELM-THEODOR-ROEMHELD-STRASSE 18 55130 MAINZ Voir sur la carte Coût total Aucune donnée ISTITUTO NAZIONALE DI STATISTICA Italie Contribution de l’UE Aucune donnée Adresse VIA CESARE BALBO 16 00184 ROMA Voir sur la carte Coût total Aucune donnée JYVAESKYLAEN YLIOPISTO Finlande Contribution de l’UE Aucune donnée Adresse SEMINAARINKATU 15 40100 JYVASKYLA Voir sur la carte Coût total Aucune donnée QANTARIS GMBH Allemagne Contribution de l’UE Aucune donnée Adresse BAHNHOFSTRASSE 7 61476 KRONBERG Voir sur la carte Coût total Aucune donnée ROYAL HOLLOWAY AND BEDFORD NEW COLLEGE Royaume-Uni Contribution de l’UE Aucune donnée Adresse EGHAM HILL TW20 0EX EGHAM, SURREY Voir sur la carte Coût total Aucune donnée STATISTICS DENMARK Danemark Contribution de l’UE Aucune donnée Adresse SEJROEGADE 11 2100 COPENHAGEN Voir sur la carte Coût total Aucune donnée STATISTICS FINLAND Finlande Contribution de l’UE Aucune donnée Adresse TYOPAJAKATU 13 00022 HELSINKI Voir sur la carte Coût total Aucune donnée SWISS FEDERAL STATISTICAL OFFICE Suisse Contribution de l’UE Aucune donnée Adresse ESPACE DE L'EUROPE 10 2010 NEUCHATEL Voir sur la carte Coût total Aucune donnée THE NUMERICAL ALGORITHMS GROUP LIMITED Royaume-Uni Contribution de l’UE Aucune donnée Adresse WILKINSON HOUSE, JORDAN HILL ROAD OX2 8DR OXFORD Voir sur la carte Coût total Aucune donnée UNIVERSITY OF SOUTHAMPTON Royaume-Uni Contribution de l’UE Aucune donnée Adresse HIGHFIELD SO17 1BJ SOUTHAMPTON Voir sur la carte Coût total Aucune donnée UNIVERSITY OF YORK Royaume-Uni Contribution de l’UE Aucune donnée Adresse HESLINGTON HALL YO10 5DD YORK Voir sur la carte Coût total Aucune donnée