research data . Dataset . 2016

The Uncertainty of Storm Season Changes: Quantifying the Uncertainty of Autocovariance Changepoints

A. D. Aston, John; F. H. Nam, Christopher; A. Eckley, Idris; Killick, Rebecca;
  • Published: 01 Jan 2016
  • Publisher: Figshare
Abstract
<div><p>In oceanography, there is interest in determining storm season changes for logistical reasons such as equipment maintenance scheduling. In particular, there is interest in capturing the uncertainty associated with these changes in terms of the number and location of them. Such changes are associated with autocovariance changes. This article proposes a framework to quantify the uncertainty of autocovariance changepoints in time series motivated by this oceanographic application. More specifically, the framework considers time series under the locally stationary wavelet (LSW) framework, deriving a joint density for scale processes in the raw wavelet period...
Subjects
free text keywords: Engineering, Medicine, Neuroscience, Earth and Environmental Sciences, Biological Sciences, Mathematics, Cancer, Inorganic Chemistry, such, density, wavelet, autocovariance, uncertainty, hmm, framework, time series, changepoint, model, LSW, storm season changes, equipment maintenance scheduling
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Dataset . 2016
Provider: figshare
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