6533b831fe1ef96bd1299892

RESEARCH PRODUCT

Imputation Strategies for Missing Data in Environmental Time Series for An Unlucky Situation

Daria Mendola

subject

Multivariate statisticsAir pollutantsComputer scienceStatisticsAutoregressive–moving-average modelImputation (statistics)Missing data

description

After a detailed review of the main specific solutions for treatment of missing data in environmental time series, this paper deals with the unlucky situation in which, in an hourly series, missing data immediately follow an absolutely anomalous period, for which we do not have any similar period to use for imputation. A tentative multivariate and multiple imputation is put forward and evaluated; it is based on the possibility, typical of environmental time series, to resort to correlations or physical laws that characterize relationships between air pollutants.

yearjournalcountryeditionlanguage
2005-11-23
http://hdl.handle.net/10447/4921