State-of-the-Art in Sequential Change-Point Detection
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چکیده
منابع مشابه
State-of-the-Art in Sequential Change-Point Detection
The problem of sequential change-point detection is concerned with the design and analysis of fastest ways to detect a change in the statistical profile of a random time process, given a tolerable risk of a false detection. The subject finds applications, e.g., in quality and process control, anomaly and failure detection, surveillance and security, finance, intrusion detection, boundary tracki...
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the problems of sequential change-point have several important applications in quality control, signal processing, and failure detection in industry and finance. we discuss a bayesian approach in the context of statistical process control: at an unknown time $tau$, the process behavior changes and the distribution of the data changes from p0 to p1. two cases are considered: (i) p0 and p1 are fu...
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For the problem of sequential change detection we propose a novel modelling of the change-point mechanism. In particular we regard the time of change as a stopping time controlled by Nature. Nature, in order to decide when to impose the change, accesses sequentially information which can be different from the information provided to the Statistician to detect the change. Using as performance me...
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Motivated from a molecular dynamics context we propose a sequential change point detection algorithm for vector-valued autoregressive models based on Bayesian model selection. The algorithm does not rely on any sampling procedure or assumptions underlying the dynamics of the transitions, and is designed to cope with high dimensional data. We show the applicability of the algorithm on a time ser...
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We develop a method for sequential detection of structural changes in linear quantile regression models. We establish the asymptotic properties of the proposed test statistic, and demonstrate the advantages of the proposed method over existing tests through simulation. © 2015 Elsevier B.V. All rights reserved.
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ژورنال
عنوان ژورنال: Methodology and Computing in Applied Probability
سال: 2011
ISSN: 1387-5841,1573-7713
DOI: 10.1007/s11009-011-9256-5