Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models

Otto, P. (2016) Detection of spatial change points in the mean and covariances of multivariate simultaneous autoregressive models. Biometrical Journal, 58(5), pp. 1113-1137. (doi: 10.1002/bimj.201500148)

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Abstract

In this paper, we propose a test procedure to detect change points of multidimensional autoregressive processes. The considered process differs from typical applied spatial autoregressive processes in that it is assumed to evolve from a predefined center into every dimension. Additionally, structural breaks in the process can occur at a certain distance from the predefined center. The main aim of this paper is to detect such spatial changes. In particular, we focus on shifts in the mean and the autoregressive parameter. The proposed test procedure is based on the likelihood-ratio approach. Eventually, the goodness-of-fit values of the estimators are compared for different shifts. Moreover, the empirical distribution of the test statistic of the likelihood-ratio test is obtained via Monte Carlo simulations. We show that the generalized Gumbel distribution seems to be a suitable limiting distribution of the proposed test statistic. Finally, we discuss the detection of lung cancer in computed tomography scans and illustrate the proposed test procedure.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Otto, Dr Philipp
Authors: Otto, P.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Biometrical Journal
Publisher:Wiley
ISSN:0323-3847
ISSN (Online):1521-4036
Published Online:04 July 2016

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