Statistics Seminar - Ery Arias-Castro

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  • Date/Time:
    • Friday October 7, 2016
      11:00 am - 12:00 pm
  • Location: ISyE Main 341
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Xiaoming Huo


Summary Sentence: Statistics Seminar - Ery Arias-Castro

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TITLE: Distribution-Free Detection of Structured Anomalies: Permutation and Rank-Based Scans


The scan statistic is by far the most popular method for anomaly detection, being popular in syndromic surveillance, signal and image processing, and target detection based on sensor networks, among other applications.  The use of the scan statistics in such settings yields a hypothesis testing procedure, where the null hypothesis corresponds to the absence of anomalous behavior.  If the null distribution is known, then calibration of a scan-based test is relatively easy, as it can be done by Monte Carlo simulation.  When the null distribution is unknown, it is less straightforward. 


We investigate two procedures.  The first one is a calibration by permutation and the other is a rank-based scan test, which is distribution-free and less sensitive to outliers.  Furthermore, the rank scan test requires only a one-time calibration for a given data size making it computationally much more appealing.  In both cases, we quantify the performance loss with respect to an oracle scan test that knows the null distribution.  We  show that using one of these calibration procedures results in only a very small loss of power in the context of a natural exponential family. This includes the classical normal location model, popular in signal processing, and the Poisson model, popular in syndromic surveillance.  We perform numerical experiments on simulated data further supporting our theory and also on a real dataset from genomics.


Joint work with Rui M. Castro(1), Ervin Tánczos(1), and Meng Wang(2)


(1) Technische Universiteit Eindhoven

(2) Stanford University


The paper is available online at

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School of Industrial and Systems Engineering (ISYE)

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  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Sep 28, 2016 - 1:51pm
  • Last Updated: Apr 13, 2017 - 5:14pm