INFERENCE FOR STRUCTURAL BREAKS IN SPATIAL MODELS
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 1961-1981 |
| Journal / Publication | Statistica Sinica |
| Volume | 32 |
| Issue number | 4 |
| Publication status | Published - Oct 2022 |
| Externally published | Yes |
Link(s)
Abstract
Testing for structural changes in spatial trends constitutes an important issue in many biomedical and geophysical applications. In this paper, a novel statistic based on a discrepancy measure over small blocks is proposed. This measure can be used not only to construct tests for structural breaks, but also to identify the change-boundaries of the breaks. The asymptotic properties and limit distributions of the proposed tests are also established. To derive the asymptotics, the notion of spatial physical dependence is adopted to account for the spatial dependence structure. A bootstrap procedure is applied to the proposed statistic to handle the asymptotic variance of the limit distribution. The method is illustrated by means of simulations and a data analysis. © 2022 Institute of Statistical Science. All rights reserved.
Research Area(s)
- Change-boundaries, discrepancy measure, inference, nonstationary processes, spatial trends
Citation Format(s)
INFERENCE FOR STRUCTURAL BREAKS IN SPATIAL MODELS. / Chan, Ngai Hang; Zhang, Rongmao; Yau, Chun Yip.
In: Statistica Sinica, Vol. 32, No. 4, 10.2022, p. 1961-1981.
In: Statistica Sinica, Vol. 32, No. 4, 10.2022, p. 1961-1981.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
