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Hotelling´s T2 Method in Multivariate On-line Surveillance. On the Delay of an Alarm

Author

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  • Andersson, Eva

    (Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University)

Abstract

A system for detecting changes in an on-going process is needed in many situations. On-line monitoring (surveillance) is used in early detection of disease outbreaks, of patients at risk and of financial instability. By continually monitoring one or several indicators, we can, early, detect a change in the processes of interest. There are several suggested methods for multivariate surveillance, one of which is the Hotelling’s T2. Since one aim in surveillance is quick detection of a change, it is important to use evaluation measures that reflect the timeliness of an alarm. One suggested measure is the expected delay of an alarm, in relation to the time of change ( ) in the process. Here we investigate a delay measure for the bivariate situation. Generally, the measure depends on both change times (i.e. 1 and 2). We show that, for a bivariate situation using the T2 method, the delay only depends on 1 and 2 through the distance 1- 2.

Suggested Citation

  • Andersson, Eva, 2008. "Hotelling´s T2 Method in Multivariate On-line Surveillance. On the Delay of an Alarm," Research Reports 2008:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    • Handle: RePEc:hhs:gunsru:2008_003
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    File URL: http://hdl.handle.net/2077/18778
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    References listed on IDEAS

    as
    1. Bock, David, 2007. "Evaluations of likelihood based surveillance of volatility," Research Reports 2007:9, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    2. Frisén, Marianne, 2007. "Principles for Multivariate Surveillance," Research Reports 2007:4, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    3. Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Similarities and differences between statistical surveillance and certain decision rules in finance," Research Reports 2007:8, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    4. Andersson, Eva & Bock, David & Frisén, Marianne, 2007. "Modeling influenza incidence for the purpose of on-line monitoring," Research Reports 2007:5, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    5. Bock, David, 2007. "Consequences of using the probability of a false alarm as the false alarm measure," Research Reports 2007:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    6. Max Petzold & Christian Sonesson & Eva Bergman & Helle Kieler, 2004. "Surveillance in Longitudinal Models: Detection of Intrauterine Growth Restriction," Biometrics, The International Biometric Society, vol. 60(4), pages 1025-1033, December.
    7. Bock, David & Andersson, Eva & Frisén, Marianne, 2007. "Statistical Surveillance of Epidemics: Peak Detection of Influenza in Sweden," Research Reports 2007:6, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    8. Eva Andersson & David Bock & Marianne Frisén, 2004. "Detection of Turning Points in Business Cycles," Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2004(1), pages 93-108.
    9. Andersson, Eva, 2007. "Effect of dependency in systems for multivariate surveillance," Research Reports 2007:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    10. Frisén, Marianne & Andersson, Eva & Schiöler, Linus, 2007. "Robust outbreak surveillance of epidemics in Sweden," Research Reports 2007:12, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
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    12. Pettersson, Kjell, 2008. "On curve estimation under order restrictions," Research Reports 2007:15, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    13. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
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    More about this item

    Keywords

    Monitoring; On-line; Surveillance; T2; Timeliness;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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