Application of smoothing spline in sinusoidal modeling
Publish Year: 1401
Type: Journal paper
Language: English
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Document National Code:
JR_JSMTA-3-2_011
Index date: 12 June 2024
Application of smoothing spline in sinusoidal modeling abstract
The sinusoidal model has many applications in time series analysis, signal processing, regression, and other phenomena that are repeated periodically. On the other hand, smoothing spline is a flexible and useful method in many fields. In this article, smoothing spline is applied to interpolate data generated from the sinusoidal model. Therefore, a sinusoidal model is considered in three general forms. Then, in a simulation study, data sets are generated from each of the sinusoidal model forms, and the effect of changing the model components is assessed. Besides, the smoothing spline method is applied to estimate the related sinusoidal model, and the performance of the smoothing spline for fitting a proper model to the sinusoidal data is studied. Furthermore, by fitting a proper sinusoidal model to each generated data set, the performance of smoothing spline is compared with the sinusoidal model. The sum of squares error criterion is applied to compare the performance of models. The simulation results illustrate that smoothing spline has better performance for model fitting to sinusoidal data.
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Application of smoothing spline in sinusoidal modeling authors
Roshanak Alimohammadi
Department of Statistics, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran