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.

翻译：本文提出了一种基于小波的周期自回归滑动平均（PARMA）时间序列分析方法。尽管傅里叶分析为周期时间序列分析提供了有效手段，但当PARMA参数非平滑变化时，该方法需要估计大量傅里叶参数。基于小波的分析有助于我们获得参数数量减少的简约模型。我们通过模拟数据集和实际数据集对此进行了验证。