6533b871fe1ef96bd12d1f31
RESEARCH PRODUCT
EOFs for gap filling in multivariate air quality data: a FDA approach
Mariantonietta RuggieriFrancesca Di SalvoAntonella PlaiaGianna Agro'subject
Settore SECS-S/01 - StatisticaFDA EOF missing data gap fillingdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2010-01-01 |