Missing data frequently happen in environmental research, usually due to faults in data acquisition, inadequate sampling or measurement error. They make difficult to determine whether the limits set by the European Community on certain indicators of air quality are fulfilled or not. Indeed, due to missing values, the number of exceedances per year of PM10, that is particulate matter 10µm or less in diameter, and other air quality indicators are often heavily underestimated, and no environmental policy is applied to protect citizen health. In this paper, we propose a non-parametric method to impute missing values inPM10 time series. It is primarily based on a local polynomial estimator of the trend-cycle in time series. We also compare the proposed method with other methods usually used in literature for the imputation of missing values in univariate time series and implemented in the R packageimputeTS.

On the Imputation of Missing Values in Univariate PM10 Time Series

Albano Giuseppina
Membro del Collaboration Group
;
La Rocca Michele
Membro del Collaboration Group
;
Perna Cira
Membro del Collaboration Group
2018-01-01

Abstract

Missing data frequently happen in environmental research, usually due to faults in data acquisition, inadequate sampling or measurement error. They make difficult to determine whether the limits set by the European Community on certain indicators of air quality are fulfilled or not. Indeed, due to missing values, the number of exceedances per year of PM10, that is particulate matter 10µm or less in diameter, and other air quality indicators are often heavily underestimated, and no environmental policy is applied to protect citizen health. In this paper, we propose a non-parametric method to impute missing values inPM10 time series. It is primarily based on a local polynomial estimator of the trend-cycle in time series. We also compare the proposed method with other methods usually used in literature for the imputation of missing values in univariate time series and implemented in the R packageimputeTS.
2018
9783319747262
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4704841
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