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The editing of statistical data: methods and techniques for the efficient detection and correction of errors and missing values
Author(s) -
De Waal Ton,
Pannekoek Jeroen,
Scholtus Sander
Publication year - 2012
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.1194
Subject(s) - computer science , smoothing , missing data , data mining , process (computing) , software , computational statistics , machine learning , programming language , computer vision
In order to produce official statistics of sufficient quality, statistical institutes carry out an extensive process of checking and correcting the data that they collect. This process is called statistical data editing. In this article, we give a brief overview of current data editing methodology. In particular, we discuss the application of selective and automatic editing procedures to improve the efficiency and timeliness of the data editing process. WIREs Comput Stat 2012, 4:204–210. doi: 10.1002/wics.1194 This article is categorized under: Statistical and Graphical Methods of Data Analysis > Data Reduction, Smoothing, and Filtering Software for Computational Statistics > Artificial Intelligence and Expert Systems Data: Types and Structure > Data Preparation and Processing