Measuring the degree of non-stationarity of a time series

Das, Sourav, and Nason, Guy P. (2016) Measuring the degree of non-stationarity of a time series. Stat, 5 (1). pp. 295-305.

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Abstract

In time series analysis, there is an extensive literature on hypothesis tests that attempt to distinguish a stationary time series from a non-stationary one. However, the binary distinction provided by a hypothesis test can be somewhat blunt when trying to determine the degree of non-stationarity of a time series. This article creates an index that estimates a degree of non-stationarity. This index might be used, for example, to classify or discriminate between series. Our index is based on measuring the roughness of a statistic estimated from the time series, which is calculated from the roughness penalty associated with a spline smoothing/penalized least-squares method. We further use a resampling technique to obtain a likely range of index values obtained from a single realization of a time series. We apply our method to ascertain and compare the non-stationarity index of the well-known earthquake and explosion data.

Item ID: 59176
Item Type: Article (Research - C1)
ISSN: 2049-1573
Keywords: Bootstrap assessment, Non-parametric regression, Time series
Copyright Information: Attribution 4.0 International (CC BY 4.0)
Date Deposited: 13 Aug 2019 01:06
FoR Codes: 01 MATHEMATICAL SCIENCES > 0104 Statistics > 010405 Statistical Theory @ 50%
01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 50%
SEO Codes: 96 ENVIRONMENT > 9610 Natural Hazards > 961099 Natural Hazards not elsewhere classified @ 100%
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