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Parametric modeling imposes rigid assumption on abstraction of physical characteristics of a phenomenon, which in case of model misspecification could give erroneous results. To address the drawbacks, efforts have been channeled on semi-parametric and nonparametric modeling and inference. This study focuses on constructing an estimator and consequently modeling a meteorological temperature time series first by constructing a penalized spline estimator based on cubic splines. The penalizeddoi:10.5539/ijsp.v9n5p61 fatcat:sdixt727nzd7noxafwexkv5h5y