IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v44y2003i1-2p223-236.html
   My bibliography  Save this article

Inferences based on multiple skipped correlations

Author

Listed:
  • Wilcox, Rand R.

Abstract

No abstract is available for this item.

Suggested Citation

  • Wilcox, Rand R., 2003. "Inferences based on multiple skipped correlations," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 223-236, October.
    • Handle: RePEc:eee:csdana:v:44:y:2003:i:1-2:p:223-236
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(03)00043-4
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. William H. Rogers & John W. Tukey, 1972. "Understanding some long‐tailed symmetrical distributions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 26(3), pages 211-226, September.
    2. Struyf, Anja & Rousseeuw, Peter J., 2000. "High-dimensional computation of the deepest location," Computational Statistics & Data Analysis, Elsevier, vol. 34(4), pages 415-426, October.
    3. Zani, Sergio & Riani, Marco & Corbellini, Aldo, 1998. "Robust bivariate boxplots and multiple outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 28(3), pages 257-270, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Christophe Croux & Catherine Dehon, 2010. "Influence functions of the Spearman and Kendall correlation measures," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 497-515, November.
    2. Nagahara, Yuichi, 2004. "A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 1-29, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Masse, Jean-Claude & Plante, Jean-Francois, 2003. "A Monte Carlo study of the accuracy and robustness of ten bivariate location estimators," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 1-26, February.
    2. Rand Wilcox, 2004. "Inferences Based on a Skipped Correlation Coefficient," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(2), pages 131-143.
    3. Xiaohui Liu & Shihua Luo & Yijun Zuo, 2020. "Some results on the computing of Tukey’s halfspace median," Statistical Papers, Springer, vol. 61(1), pages 303-316, February.
    4. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2015. "Multivariate functional outlier detection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 177-202, July.
    5. Lachos, Victor H. & Prates, Marcos O. & Dey, Dipak K., 2021. "Heckman selection-t model: Parameter estimation via the EM-algorithm," Journal of Multivariate Analysis, Elsevier, vol. 184(C).
    6. Aldo Corbellini & Marco Riani & Anthony Atkinson, 2015. "Hubert, Rousseeuw and Segaert: multivariate functional outlier detection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 257-261, July.
    7. Chanont Banternghansa & Michael W. McCracken, 2009. "Forecast disagreement among FOMC members," Working Papers 2009-059, Federal Reserve Bank of St. Louis.
    8. Cerioli, Andrea & Farcomeni, Alessio & Riani, Marco, 2014. "Strong consistency and robustness of the Forward Search estimator of multivariate location and scatter," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 167-183.
    9. Talha Arslan, 2021. "An α -Monotone Generalized Log-Moyal Distribution with Applications to Environmental Data," Mathematics, MDPI, vol. 9(12), pages 1-18, June.
    10. Hazan, Alon & Landsman, Zinoviy & E Makov, Udi, 2003. "Robustness via a mixture of exponential power distributions," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 111-121, February.
    11. Anthony Atkinson & Marco Riani, 2004. "The forward search and data visualisation," Computational Statistics, Springer, vol. 19(1), pages 29-54, February.
    12. Bickel, David R., 2002. "Robust estimators of the mode and skewness of continuous data," Computational Statistics & Data Analysis, Elsevier, vol. 39(2), pages 153-163, April.
    13. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2017. "Multivariate and functional classification using depth and distance," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(3), pages 445-466, September.
    14. Chi Ng & Johan Lim & Kyeong Lee & Donghyeon Yu & Sujung Choi, 2014. "A fast algorithm to sample the number of vertexes and the area of the random convex hull on the unit square," Computational Statistics, Springer, vol. 29(5), pages 1187-1205, October.
    15. Vilijandas Bagdonavičius & Linas Petkevičius, 2020. "A new multiple outliers identification method in linear regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(3), pages 275-296, April.
    16. Bellini, Tiziano, 2012. "Forward search outlier detection in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 216(1), pages 200-207.
    17. Riani, Marco & Perrotta, Domenico & Cerioli, Andrea, 2015. "The Forward Search for Very Large Datasets," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(c01).
    18. Fan Chen & Guy Nason, 2020. "A new method for computing the projection median, its influence curve and techniques for the production of projected quantile plots," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-22, May.
    19. Pilar A. Rivera & Diego I. Gallardo & Osvaldo Venegas & Marcelo Bourguignon & Héctor W. Gómez, 2021. "An Extension of the Truncated-Exponential Skew- Normal Distribution," Mathematics, MDPI, vol. 9(16), pages 1-11, August.
    20. Verdonck, T. & Van Wouwe, M., 2011. "Detection and correction of outliers in the bivariate chain-ladder method," Insurance: Mathematics and Economics, Elsevier, vol. 49(2), pages 188-193, September.

    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:eee:csdana:v:44:y:2003:i:1-2:p:223-236. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.