IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v62y2000i1p117-135.html
   My bibliography  Save this article

Extremal analysis of processes sampled at different frequencies

Author

Listed:
  • M. E. Robinson
  • J. A. Tawn

Abstract

The observed extremes of a discrete time process depend on the process itself and the sampling frequency. We develop theoretical results which show how to account for the effect of sampling frequency on extreme values, thus enabling us to analyse systematically extremal data from series with different sampling rates. We present statistical methodology based on these results which we illustrate though simulations and by applications to sea‐waves and rainfall data.

Suggested Citation

  • M. E. Robinson & J. A. Tawn, 2000. "Extremal analysis of processes sampled at different frequencies," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 117-135.
    • Handle: RePEc:bla:jorssb:v:62:y:2000:i:1:p:117-135
    DOI: 10.1111/1467-9868.00223
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-9868.00223
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-9868.00223?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hall, A. & Scotto, M. G., 2003. "Extremes of sub-sampled integer-valued moving average models with heavy-tailed innovations," Statistics & Probability Letters, Elsevier, vol. 63(1), pages 97-105, May.
    2. Scotto, M. G., 2003. "A note on the asymptotic distribution of the maxima in disaggregated time-series models," Statistics & Probability Letters, Elsevier, vol. 65(2), pages 127-137, November.
    3. Gomes, M. Ivette & Hall, Andreia & Miranda, M. Cristina, 2008. "Subsampling techniques and the Jackknife methodology in the estimation of the extremal index," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2022-2041, January.
    4. Silius M. Vandeskog & Sara Martino & Daniela Castro-Camilo & Håvard Rue, 2022. "Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 598-621, December.
    5. M. G. Scotto & K. F. Turkman & C. W. Anderson, 2003. "Extremes of Some Sub‐Sampled Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(5), pages 579-590, September.
    6. Paola Bortot & Carlo Gaetan, 2016. "Latent Process Modelling of Threshold Exceedances in Hourly Rainfall Series," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 531-547, September.
    7. Wimmer, Werenfrid & Challenor, Peter & Retzler, Chris, 2006. "Extreme wave heights in the North Atlantic from Altimeter Data," Renewable Energy, Elsevier, vol. 31(2), pages 241-248.
    8. John G. Galbraith & Serguei Zernov, 2006. "Extreme Dependence In The Nasdaq And S&P Composite Indexes," Departmental Working Papers 2006-14, McGill University, Department of Economics.
    9. Scotto, M., 2005. "Extremes of a class of deterministic sub-sampled processes with applications to stochastic difference equations," Stochastic Processes and their Applications, Elsevier, vol. 115(3), pages 417-434, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssb:v:62:y:2000:i:1:p:117-135. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.