Seasonal time-series imputation of gap missing algorithm (STIGMA)
This work presents a new approach for the imputation of missing data in weather time-series from a seasonal pattern; the seasonal time-series imputation of gap missing algorithm (STIGMA). The algorithm takes advantage from a seasonal pattern for the imputation of unknown data by averaging available data. We test the algorithm using data measured every minutes over a period of days during the year 2010; the variables include global irradiance, diffuse irradiance, ultraviolet irradiance, and temperature,...