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Editorial for the special issue: Change point detection

Author

Listed:
  • Georgy Sofronov

    (Macquarie University)

  • Martin Wendler

    (Otto-von-Guericke-Universität)

  • Volkmar Liebscher

    (Universität Greifswald)

Abstract

No abstract is available for this item.

Suggested Citation

  • Georgy Sofronov & Martin Wendler & Volkmar Liebscher, 2020. "Editorial for the special issue: Change point detection," Statistical Papers, Springer, vol. 61(4), pages 1347-1349, August.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:4:d:10.1007_s00362-020-01199-9
    DOI: 10.1007/s00362-020-01199-9
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    References listed on IDEAS

    as
    1. Alfredas Račkauskas & Martin Wendler, 2020. "Convergence of U-processes in Hölder spaces with application to robust detection of a changed segment," Statistical Papers, Springer, vol. 61(4), pages 1409-1435, August.
    2. Gapeev, Pavel V., 2020. "On the problems of sequential statistical inference for Wiener processes with delayed observations," LSE Research Online Documents on Economics 104072, London School of Economics and Political Science, LSE Library.
    3. Christoph Bandt, 2020. "Order patterns, their variation and change points in financial time series and Brownian motion," Statistical Papers, Springer, vol. 61(4), pages 1565-1588, August.
    4. Krzysztof J. Szajowski, 2020. "Rationalization of detection of the multiple disorders," Statistical Papers, Springer, vol. 61(4), pages 1545-1563, August.
    5. Maria Mohr & Leonie Selk, 2020. "Estimating change points in nonparametric time series regression models," Statistical Papers, Springer, vol. 61(4), pages 1437-1463, August.
    6. Pavel V. Gapeev, 2020. "On the problems of sequential statistical inference for Wiener processes with delayed observations," Statistical Papers, Springer, vol. 61(4), pages 1529-1544, August.
    7. Qing Yang & Yu-Ning Li & Yi Zhang, 2020. "Change point detection for nonparametric regression under strongly mixing process," Statistical Papers, Springer, vol. 61(4), pages 1465-1506, August.
    8. Lijing Ma & Andrew J. Grant & Georgy Sofronov, 2020. "Multiple change point detection and validation in autoregressive time series data," Statistical Papers, Springer, vol. 61(4), pages 1507-1528, August.
    Full references (including those not matched with items on IDEAS)

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