Properties of stationary cyclical processes

Fuente: arXiv
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Main Author: Lenart, Łukasz
Format: Preprint
Published: 2024
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author Lenart, Łukasz
author_facet Lenart, Łukasz
contents The paper investigates the theoretical properties of zero-mean stationary time series with cyclical components, admitting the representation $y_t=α_t \cos λt + β_t \sin λt$, with $λ\in (0,π]$ and $[α_t\,\, β_t]$ following some bivariate process. We diagnose that in the extant literature on cyclic time series, a prevalent assumption of Gaussianity for $[α_t\,\, β_t]$ imposes inadvertently a severe restriction on the amplitude of the process. Moreover, it is shown that other common distributions may suffer from either similar defects or fail to guarantee the stationarity of $y_t$. To address both of the issues, we propose to introduce a direct stochastic modulation of the amplitude and phase shift in an almost periodic function. We prove that this novel approach may lead, in general, to a stationary (up to any order) time series, and specifically, to a zero-mean stationary time series featuring cyclicity, with a pseudo-cyclical autocovariance function that may even decay at a very slow rate. The proposed process fills an important gap in this type of models and allows for flexible modeling of amplitude and phase shift.
format Preprint
id arxiv_https___arxiv_org_abs_2405_08907
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Properties of stationary cyclical processes
Lenart, Łukasz
Statistics Theory
Methodology
G.3
The paper investigates the theoretical properties of zero-mean stationary time series with cyclical components, admitting the representation $y_t=α_t \cos λt + β_t \sin λt$, with $λ\in (0,π]$ and $[α_t\,\, β_t]$ following some bivariate process. We diagnose that in the extant literature on cyclic time series, a prevalent assumption of Gaussianity for $[α_t\,\, β_t]$ imposes inadvertently a severe restriction on the amplitude of the process. Moreover, it is shown that other common distributions may suffer from either similar defects or fail to guarantee the stationarity of $y_t$. To address both of the issues, we propose to introduce a direct stochastic modulation of the amplitude and phase shift in an almost periodic function. We prove that this novel approach may lead, in general, to a stationary (up to any order) time series, and specifically, to a zero-mean stationary time series featuring cyclicity, with a pseudo-cyclical autocovariance function that may even decay at a very slow rate. The proposed process fills an important gap in this type of models and allows for flexible modeling of amplitude and phase shift.
title Properties of stationary cyclical processes
topic Statistics Theory
Methodology
G.3
url https://arxiv.org/abs/2405.08907