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.
|
PDF (Published Version)
- Published Version
Available under License Creative Commons Attribution. Download (995kB) | Preview |
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: | 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490509 Statistical theory @ 50% 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490511 Time series and spatial modelling @ 50% |
| SEO Codes: | 96 ENVIRONMENT > 9610 Natural Hazards > 961099 Natural Hazards not elsewhere classified @ 100% |
| Downloads: |
Total: 1037 Last 12 Months: 4 |
| More Statistics |
Actions (Repository Staff Only)
 |
Item Control Page |