A note on state space representations of locally stationary wavelet time series

Simple item page
dc.creatorTriantafyllopoulos, K.
dc.creatorNason, G. P.
dc.date2008-07-19
dc.date.accessioned2026-07-07T12:34:15Z
dc.date.available2026-07-07T12:34:15Z
dc.descriptionIn this note we show that the locally stationary wavelet process can be decomposed into a sum of signals, each of which following a moving average process with time-varying parameters. We then show that such moving average processes are equivalent to state space models with stochastic design components. Using a simple simulation step, we propose a heuristic method of estimating the above state space models and then we apply the methodology to foreign exchange rates data.
dc.description8 pages, 3 figures
dc.identifierhttps://arxiv.org/abs/0807.3113
dc.identifierhttp://arxiv.org/abs/0807.3113
dc.identifierStatistics and Probability Letters (2009), 79, pp. 50-54.
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/217358
dc.subjectMethodology
dc.subjectApplications
dc.titleA note on state space representations of locally stationary wavelet time series
dc.typetext

Files

Collections

arXiv