Single interpolation: A review of application in air quality data sets

Abstract

The Single imputation methods have been wide-used techniques among researchers in the field of missing data in environmental data sets. Usually, ignorable the missing data and discard those incomplete cases in data sets as approach. However, this is not suitable for time-series prediction especially for air quality data sets. From the literatures study, has a valid method to predict the missing data in air pollutant data sets, its interpolation method. Interpolation as a well known problem in numerical method and it has been used in difference approaches in environmental data sets. The purpose of this paper is to present an overview of the existing literature about single interpolation techniques assessment to predict missing data in data air pollutant sets.