Assessment of single imputation methods for replacement of missing value in air pollution monitoring record - Mohd Lutfi Zainudin (School of Environmental Engineering, 2011)
Generally, air pollution data are recorded in term of time series plot and characterize by many fluctuations and presented with continuously data. However, usually the problems encountered in time series analysis is missing value and this situation frequently happens in air pollution time series data. This problem arises from insufficient sampling, error in measurement or faults in data acquisition. On this condition, imputation method adoption is necessary to replace the missing values in the data set. In this research, various single imputation methods were used to replace the missing value in time series data sets. Two (2) types of single imputation methods were used that are interpolation methods (Lagrange interpolation, linear interpolation and Bessel interpolation) and mean imputation techniques (arithmetic mean, diurnal hour mean and daily mean).