IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v42y2001i2p265-273.html
   My bibliography  Save this article

Error rates in classification consisting of discrete and continuous variables in the presence of covariates

Author

Listed:
  • Chi-Ying Leung

Abstract

No abstract is available for this item.

Suggested Citation

  • Chi-Ying Leung, 2001. "Error rates in classification consisting of discrete and continuous variables in the presence of covariates," Statistical Papers, Springer, vol. 42(2), pages 265-273, April.
    • Handle: RePEc:spr:stpapr:v:42:y:2001:i:2:p:265-273
    DOI: 10.1007/s003620100055
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s003620100055
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s003620100055?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
    ---><---

    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. N. Balakrishnan & M. Tiku, 1988. "Robust classification procedures based on dichotomous and continuous variables," Journal of Classification, Springer;The Classification Society, vol. 5(1), pages 53-80, March.
    2. Krzanowski, W. J., 1994. "Quadratic location discriminant functions for mixed categorical and continuous data," Statistics & Probability Letters, Elsevier, vol. 19(2), pages 91-95, January.
    3. Chi-Ying Leung, 1998. "The Covariance Adjusted Location Linear Discriminant Function for Classifying Data with Unequal Dispersion Matrices in Different Locations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 50(3), pages 417-431, September.
    4. Leung, Chi-Ying, 1996. "The location linear discriminant for classifying observations with unequal variances," Statistics & Probability Letters, Elsevier, vol. 31(1), pages 23-29, December.
    5. W. Krzanowski, 1993. "The location model for mixtures of categorical and continuous variables," Journal of Classification, Springer;The Classification Society, vol. 10(1), pages 25-49, January.
    Full references (including those not matched with items on IDEAS)

    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. Leung, Chi-Ying, 2003. "The effect of across-location heteroscedasticity on the classification of mixed categorical and continuous data," Journal of Multivariate Analysis, Elsevier, vol. 84(2), pages 369-386, February.
    2. Leung, Chi-Ying, 2005. "Regularized classification for mixed continuous and categorical variables under across-location heteroscedasticity," Journal of Multivariate Analysis, Elsevier, vol. 93(2), pages 358-374, April.
    3. A. R. de Leon & A. Soo & T. Williamson, 2011. "Classification with discrete and continuous variables via general mixed-data models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 1021-1032, February.
    4. Thomas Bittmann & Jens‐Peter Loy & Sven Anders, 2020. "Product differentiation and cost pass‐through: industry‐wide versus firm‐specific cost shocks," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1184-1209, October.
    5. Colin O. Wu & Gang Zheng & Minjung Kwak, 2013. "A Joint Regression Analysis for Genetic Association Studies with Outcome Stratified Samples," Biometrics, The International Biometric Society, vol. 69(2), pages 417-426, June.
    6. Leung, Chi-Ying, 1999. "Covariance Adjustments in Discrimination of Mixed Discrete and Continuous Variables," Journal of Multivariate Analysis, Elsevier, vol. 71(1), pages 111-124, October.
    7. Sudha Bishnoi & Nadhir Al-Ansari & Mujahid Khan & Salim Heddam & Anurag Malik, 2022. "Classification of Cotton Genotypes with Mixed Continuous and Categorical Variables: Application of Machine Learning Models," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    8. Marian Núñez & Angel Villarroya & José María Oller, 2003. "Minimum Distance Probability Discriminant Analysis for Mixed Variables," Biometrics, The International Biometric Society, vol. 59(2), pages 248-253, June.
    9. Layal Christine Lettry, 2023. "Clustering the Swiss Pension Register," FSES Working Papers 529, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    10. Nor Mahat & W.J. Krzanowski & A. Hernandez, 2009. "Strategies for Non-Parametric Smoothing of the Location Model in Mixed-Variable Discriminant Analysis," Modern Applied Science, Canadian Center of Science and Education, vol. 3(1), pages 151-151, January.
    11. Merbouha, A. & Mkhadri, A., 2004. "Regularization of the location model in discrimination with mixed discrete and continuous variables," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 563-576, April.
    12. Pan Shenyi & Joe Harry, 2024. "Assessing copula models for mixed continuous-ordinal variables," Dependence Modeling, De Gruyter, vol. 12(1), pages 1-18.
    13. W. Krzanowski, 1993. "The location model for mixtures of categorical and continuous variables," Journal of Classification, Springer;The Classification Society, vol. 10(1), pages 25-49, January.

    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:spr:stpapr:v:42:y:2001:i:2:p:265-273. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.