Application of smoothing spline in sinusoidal modeling

Document Type : Original Scientific Paper

Author

Department of Statistics‎, ‎Faculty of Mathematical Sciences‎, ‎Alzahra University‎, ‎Tehran‎, ‎Iran

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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References

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Journal of Statistical Modelling: Theory and Applications
Volume 3, Issue 2
July 2022
Pages 169-173

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History

  • Receive Date: 15 July 2023
  • Revise Date: 22 November 2023
  • Accept Date: 25 November 2023

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