This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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417
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Defense and National Security
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Abstract - #307411 |
Title:
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An Investigation of Locality Region for Scan Statistics in a Time Series of Graphs
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Author(s):
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Kristin Ash*+ and David J. Marchette and Carey E. Priebe
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Companies:
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Naval Surface Warfare Center and Naval Surface Warfare Center and The Johns Hopkins University
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Address:
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, , ,
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Keywords:
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scan statistic ;
graph time series ;
random graph ;
locality statistic ;
stochastic model
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Abstract:
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Scan statistics provide a means of discovering changes and anomalies in a time series of graphs. Given a locality statistic (in our case the size of the induced subgraph of N[v], the neighborhood at a vertex), the scan statistic is the maximum locality statistic for a given graph. Taking a window of time W up to current time, we consider four of the possible definitions of neighborhood over a time series of graphs: N[v] in the current graph; N[v] in the current graph applied to each graph in W; the union and intersection of all N[v] in W. Each method has power under different assumptions. We compare these in a simple change point detection problem: the detection of a small anomalous region. We discuss a stochastic model for the generation of a time series of random graphs and explore the performance of the different neighborhood approaches as a function of the parameters of the model.
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