Zoekresultaten

National statistical institutes try to construct data sets that are rich in information content by combining available data as much as possible. Unfortunately, units, e.g. persons or enterprises, in...

Error localization is the problem of finding out which fields in raw data records contain erroneous values. The editrules extension package for the R environment forstatistical computing was recently...

Data cleaning, or data preparation is an essential part of statistical analysis. In fact, in practice it is often more time-consuming than the statistical analysis itself. These lecture notes...

The quality of statistical statements strongly depends on the quality of the underlying data. Since raw data is often inconsistent or incomplete, data editing may consume a substantial amount of the...

Numerical and categorical data used for statistical analyses is often plagued with missing values and inconsistencies. In many cases, a number of missing values may be derived, based on the...

Analyses of categorical data are often hindered by the occurrence of inconsistent or incomplete raw data. Although R has many features for analyzing categorical data, the functionality for error...

Since raw (survey) data usually has to be edited before statistical analysis can take place, the availability of data cleaning algorithms is important to many statisticians. In this paper the...

From July to December 2005 a large scale follow up of nonrespondents in the Dutch Labour Force Survey (LFS) was conducted at Statistics Netherlands. In the study a sample of non-respondents in the...

Timmerman, Jolanda G. and Peter J.M. van de Ven (1994).