6533b86cfe1ef96bd12c8b9c

RESEARCH PRODUCT

Empirical Orthogonal Function and Functional Data Analysis Procedures to Impute Long Gaps in Environmental Data

Mariantonietta RuggieriFrancesca Di SalvoAntonella PlaiaGianna Agrò

subject

Multivariate statisticsComputer scienceFunctional data analysisEmpirical orthogonal functionsMissing datacomputer.software_genreEnvironmental dataEOF FDA Missing data Environmental dataSet (abstract data type)Singular value decompositionPerformance indicatorData miningSettore SECS-S/01 - Statisticacomputer

description

Air pollution data sets are usually spatio-temporal multivariate data related to time series of different pollutants recorded by a monitoring network. To improve the estimate of functional data when missing values, and mainly long gaps, are present in the original data set, some procedures are here proposed considering jointly Functional Data Analysis and Empirical Orthogonal Function approaches. In order to compare and validate the proposed procedures, a simulation plan is carried out and some performance indicators are computed. The obtained results show that one of the proposed procedures works better than the others, providing a better reconstruction especially in presence of long gaps.

yearjournalcountryeditionlanguage
2016-01-01
10.1007/978-3-319-27274-0_1http://hdl.handle.net/10447/202492