Functional data analysis: A review of smoothing techniques.

In this age of growing Functional Data Analysis (FDA) procedures, it might be challenging to express time series data using the basis functions that are often used in the FDA smoothing techniques due to the rigidity of existing methods. Thus, it is essential to develop advanced smoothing techniques to interpret massive data sets flexibly and to portray the data accurately in functional form. In this study, a comprehensive systematic literature review was done between 2018 and 2023 by focusing on smoothing techniques applied in FDA. The contributions of this study are on (1) the advantages and disadvantages of the techniques and (2) the current trend and future direction of the study. In conclusion, this study demonstrates the significance of the FDA in a wide range of sectors, the advantages, and disadvantages of smoothing techniques for time series data, and its significance issues. Since the FDA makes no assumptions regarding the data, applying it to all time-series studies should improve the modeling technique. [ABSTRACT FROM AUTHOR]