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Extreme Value Asymptotics for Multivariate Renewal Processes

Author

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  • Steinebach, Josef
  • Eastwood, Vera R.

Abstract

For a sequence of partial sums ofd-dimensional independent identically distributed random vectors a corresponding multivariate renewal process is defined componentwise. Via strong invariance together with an extreme value limit theorem for Rayleigh processes, a number of weak asymptotic results are established for thed-dimensional renewal process. Similar theorems for the estimated version of this process are also derived. These results are suggested to serve as simultaneous asymptotic testing devices for detecting changes in the multivariate setting.

Suggested Citation

  • Steinebach, Josef & Eastwood, Vera R., 1996. "Extreme Value Asymptotics for Multivariate Renewal Processes," Journal of Multivariate Analysis, Elsevier, vol. 56(2), pages 284-302, February.
    • Handle: RePEc:eee:jmvana:v:56:y:1996:i:2:p:284-302
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    Cited by:

    1. Cho, Haeran & Kirch, Claudia, 2024. "Data segmentation algorithms: Univariate mean change and beyond," Econometrics and Statistics, Elsevier, vol. 30(C), pages 76-95.
    2. Horváth, Lajos & Kokoszka, Piotr & Steinebach, Josef, 1999. "Testing for Changes in Multivariate Dependent Observations with an Application to Temperature Changes," Journal of Multivariate Analysis, Elsevier, vol. 68(1), pages 96-119, January.

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