Missing values are a common concern in spatiotemporal data sets. During recent years a great number of methods have been developed for gap filling. One of the emerging approaches is based on the Empirical Orthogonal Function (EOF) methodology, applied mainly on raw and univariate data sets presenting irregular missing patterns. In this paper EOF is carried out on a multivariate space-time data set, related to concentrations of pollutants recorded at different sites, after denoising raw data by FDA approach. Some performance indicators are computed on simulated incomplete data sets with also long gaps in order to show that the EOF reconstruction appears to be an improved procedure especially when long gap sequences occur.

Ruggieri, M., Di Salvo, F., Plaia, A., Agrò, G. (2010). EOFs for gap filling in multivariate air quality data: a FDA approach. In Proceedings of COMPSTAT 2010 (pp.1557-1564). Heidelberg : Physica-Verlag.

EOFs for gap filling in multivariate air quality data: a FDA approach

RUGGIERI, Mariantonietta;DI SALVO, Francesca;PLAIA, Antonella;AGRO', Gianna
2010-01-01

Abstract

Missing values are a common concern in spatiotemporal data sets. During recent years a great number of methods have been developed for gap filling. One of the emerging approaches is based on the Empirical Orthogonal Function (EOF) methodology, applied mainly on raw and univariate data sets presenting irregular missing patterns. In this paper EOF is carried out on a multivariate space-time data set, related to concentrations of pollutants recorded at different sites, after denoising raw data by FDA approach. Some performance indicators are computed on simulated incomplete data sets with also long gaps in order to show that the EOF reconstruction appears to be an improved procedure especially when long gap sequences occur.
Settore SECS-S/01 - Statistica
23-ago-2010
Compstat 2010
Parigi
22-27 agosto 2010
19
2010
8
http://www-roc.inria.fr/axis/COMPSTAT2010/
Ruggieri, M., Di Salvo, F., Plaia, A., Agrò, G. (2010). EOFs for gap filling in multivariate air quality data: a FDA approach. In Proceedings of COMPSTAT 2010 (pp.1557-1564). Heidelberg : Physica-Verlag.
Proceedings (atti dei congressi)
Ruggieri, M; Di Salvo, F; Plaia, A; Agrò, G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/52895
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