A novel change point approach for the detection of gas emission sources using remotely contained concentration data

Eckley, Idris and Kirch, Claudia and Weber, Silke (2020) A novel change point approach for the detection of gas emission sources using remotely contained concentration data. Annals of Applied Statistics. ISSN 1932-6157 (In Press)

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Abstract

Motivated by an example from remote sensing of gas emission sources, we derive two novel change point procedures for multivariate time series where, in contrast to classical change point literature, the changes are not required to be aligned in the different components of the time series. Instead the change points are described by a functional relationship where the precise shape depends on unknown parameters of interest such as the source of the gas emission in the above example. Two different types of tests and the corresponding estimators for the unknown parameters describing the change locations are proposed. We derive the null asymptotics for both tests under weak assumptions on the error time series and show asymptotic consistency under alternatives. Furthermore, we prove consistency for the corresponding estimators of the parameters of interest. The small sample behavior of the methodology is assessed by means of a simulation study and the above remote sensing example analyzed in detail.

Item Type:
Journal Article
Journal or Publication Title:
Annals of Applied Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1804
Subjects:
ID Code:
143048
Deposited By:
Deposited On:
08 Apr 2020 08:25
Refereed?:
Yes
Published?:
In Press
Last Modified:
12 Jul 2020 08:39