Düsterhus, André and Hense, Andreas (2012) Advanced information criterion for environmental data quality assurance. Advances in Science and Research, 8 (1). pp. 99-104. ISSN 1992-0628

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Abstract

A new method for testing time series of environmental data for internal inconsistencies is presented. The method divides the dataset into several disjunct blocks. By means of a comparison of the blocks' estimated probability density distributions, each block is compared with the others. In order to judge the differences, four different measures are used and compared: Kullback-Leibler Divergence, Jensen-Shannon Divergence, Earth Mover's Distance and the Root Mean Square. By looking at the resulting patterns, conclusions on possible inconsistencies in the data can be drawn. This paper shows some sensitivitiy tests and gives an example for an application to real data. Furthermore, it is shown, in which cases of errors (shift in mean, shift in variance and rounding), which measure performs best.

Item Type:	Article
Additional Information:	This paper was presented at the 11th EMS Annual Meeting and 10th European Conference on Applications of Meteorology (ECAM), 12 – 16 September 2011, Berlin, Germany.
Keywords:	environmental data; internal inconsistencies; Kullback-Leibler Divergence; Jensen-Shannon Divergence; Earth Mover's Distance; Root Mean Square; sensitivitiy tests; data measurement;
Academic Unit:	Faculty of Social Sciences > Geography
Item ID:	12290
Identification Number:	https://doi.org/10.5194/asr-8-99-2012
Depositing User:	André Düsterhus
Date Deposited:	30 Jan 2020 12:35
Journal or Publication Title:	Advances in Science and Research
Publisher:	Copernicus Publications
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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