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Conference of the International Society for Non-Parametric Statistics

ISNPS 2016: Nonparametric Statistics pp 323–336Cite as

Fourier-Type Monitoring Procedures for Strict Stationarity

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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 250))

Abstract

We consider model-free monitoring procedures for strict stationarity of a given time series. The new criteria are formulated as L2-type statistics incorporating the empirical characteristic function. Monte Carlo results as well as an application to financial data are presented.

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Author information

Authors and Affiliations

  1. Department of Statistics, Seoul National University, Seoul, South Korea

    S. Lee

  2. National and Kapodistrian University of Athens, Athens, Greece

    S. G. Meintanis

  3. Unit for Business Mathematics and Informatics, North-West University, Potchefstroom, South Africa

    S. G. Meintanis

  4. Unit for Business Mathematics and Informatics, North-West University, Potchefstroom, South Africa

    C. Pretorius

Authors
  1. S. Lee
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  2. S. G. Meintanis
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  3. C. Pretorius
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Corresponding author

Correspondence to C. Pretorius .

Editor information

Editors and Affiliations

  1. MODAL’X, Paris West University Nanterre La Défense, Nanterre, France

    Patrice Bertail

  2. LMA, Avignon University, Avignon, France

    Delphine Blanke

  3. MIASHS, University of Rennes 2, Rennes, France

    Pierre-André Cornillon

  4. Formation Continue CEPE, Ecole Nationale de la Statistique et de l’Administration, Malakoff, France

    Eric Matzner-Løber

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Lee, S., Meintanis, S.G., Pretorius, C. (2018). Fourier-Type Monitoring Procedures for Strict Stationarity. In: Bertail, P., Blanke, D., Cornillon, PA., Matzner-Løber, E. (eds) Nonparametric Statistics. ISNPS 2016. Springer Proceedings in Mathematics & Statistics, vol 250. Springer, Cham. https://doi.org/10.1007/978-3-319-96941-1_22

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