Wavelet Based Periodic Autoregressive Moving Average Models
Methodology
2024-03-04 v1 Statistics Theory
Statistics Theory
Abstract
This paper proposes a wavelet-based method for analysing periodic autoregressive moving average (PARMA) time series. Even though Fourier analysis provides an effective method for analysing periodic time series, it requires the estimation of a large number of Fourier parameters when the PARMA parameters do not vary smoothly. The wavelet-based analysis helps us to obtain a parsimonious model with a reduced number of parameters. We have illustrated this with simulated and actual data sets.
Keywords
Cite
@article{arxiv.2403.00281,
title = {Wavelet Based Periodic Autoregressive Moving Average Models},
author = {Rhea Davis and N. Balakrishna},
journal= {arXiv preprint arXiv:2403.00281},
year = {2024}
}