Zoekresultaten
Resultaat 1 - 17 (van 17)
A.G. de Waal Afronden van tabellen: een methode om de privacy van respondenten te beschermen
Non-fictie
Nederlands | 14 pagina's | CBS, Centraal Bureau voor de Statistiek, Voorburg | 1999
Gedrukt boek
A.G. de Waal Integratie van databronnen: het combineren van meerdere legpuzzels
Non-fictie
Nederlands | 40 pagina's | Tilburg University, [Tilburg] | 2015
Gedrukt boek
A.G. de Waal An overview of statistical data editing
This paper gives an overview of statistical data editing. The paper first describes the traditional interactive approach to data editing. It then focuses on modern editing techniques, such as selective editing, automatic editing, and macro-editing. The paper aims to provide an introduction to these topics, and give many references to the literature
Non-fictie
Engels | 43 pagina's | CBS, Statistics Netherlands, The Hague [etc.] | 2008
Gedrukt boek
Ronan Quere | A.G. de Waal Error localization in mixed data sets
Non-fictie
Engels | Statistics Netherlands, Voorburg | 2000
Gedrukt boek
J. Pannekoek | A.G. de Waal Automatic edit and imputation for business surveys: the Dutch contributions to the Eurodit project
Paper describes the general approach applied by Statistics Netherlands on the two business surveys used in the Euredit project, and the development of the edit and imputation strategy. Furthermore the paper provides results of the approach on the two evaluation data sets, and compares these results to the results of the other institutes participating in Euredit
Non-fictie
Engels | 33 pagina's | Statistics Netherlands, Voorburg [etc.] | 2003
Gedrukt boek
A.G. de Waal Development of modern edit and imputation methods at Statistics Netherlands
Non-fictie
Engels | 13 pagina's | Statistics Netherlands, Voorburg | 2002
Gedrukt boek
A.G. de Waal Automatic edit and imputation in categorical continuous and integer data
Non-fictie
Engels | 33 pagina's | Statistics Netherlands, Voorburg | 2001
Gedrukt boek
A.G. de Waal Potential improvements in LEO/Cherrie Pie and ECS
Non-fictie
Engels | 23 pagina's | Statistics Netherlands, Voorburg | 2001
Gedrukt boek
A.G. de Waal | Jos de Waard | Rogier Plomp Manual WAID (4.1)
Non-fictie
Engels | 39 pagina's | Statistics Netherlands, Voorburg | 2001
Gedrukt boek
A.G. de Waal SLICE: a software framework for statistical data editing and imputation
Non-fictie
Engels | 11 pagina's | Statistics Netherlands, Voorburg | 2000
Gedrukt boek
A.G. de Waal SLICE: generalised software for statistical data editing and imputation
Statistical offices have to face the problem that data collected by surveys or obtained from administrative registers generally contain errors as well as the problem that values in data sets obtained from these sources may be missing. To handle such errors and missing data efficiently Statistics Netherlands is currently developing a software package, called SLICE (Statistical Localisation. Imputation and Correction of Errors). SLICE will contain several edit and imputation modules. Examples are a...
Non-fictie
Engels | 7 pagina's | Statistics Netherlands, Voorburg | 2000
Gedrukt boek
A.G. de Waal An optimality proof of Statistics Netherlands' new algorithm for automatic editing of mixed data
Non-fictie
Engels | 13 pagina's | Statistics Netherlands, Voorburg | 2000
Gedrukt boek
A.G. de Waal From WAID trees to a software package for automatic imputation
Non-fictie
Engels | 8 pagina's | CBS, Voorburg | 1999
Gedrukt boek
A.G. de Waal Mathematical programming techniques for solving the general error localisation problem
Non-fictie
Engels | 23 pagina's | Statistics Netherlands, Voorburg | 1998
Gedrukt boek
J. Pannekoek | A.G. de Waal Small area estimators in statistical disclosure control
Non-fictie
Engels | 18 pagina's | Statistics Netherlands, Voorburg | 1998
Gedrukt boek
A.G. de Waal | Leon Willenborg SDC measures and information loss for microdata sets
Non-fictie
Engels | 15 pagina's | CBS, Voorburg | 1996
Gedrukt boek
Wieger Coutinho | A.G. de Waal | Marco Remmerswaal Imputation of numerical data under linear edit restrictions
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 statistical data often have to satisfy certain edit rules, which for numerical data usually take the form of linear restrictions. Standard imputation methods for numerical data as described in the literature generally do not take such linear edit restrictions...
Non-fictie
Engels | 25 pagina's | CBS, Statistics Netherlands, Voorburg [etc.] | 2007
Gedrukt boek