IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v50y2006i3p783-802.html
   My bibliography  Save this article

Identification of interaction patterns and classification with applications to microarray data

Author

Listed:
  • Boulesteix, Anne-Laure
  • Tutz, Gerhard

Abstract

No abstract is available for this item.

Suggested Citation

  • Boulesteix, Anne-Laure & Tutz, Gerhard, 2006. "Identification of interaction patterns and classification with applications to microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 783-802, February.
    • Handle: RePEc:eee:csdana:v:50:y:2006:i:3:p:783-802
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(04)00300-7
    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. Dudoit S. & Fridlyand J. & Speed T. P, 2002. "Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 77-87, March.
    2. Chris J. Lloyd, 2000. "Regression Models for Convex ROC Curves," Biometrics, The International Biometric Society, vol. 56(3), pages 862-867, September.
    3. E. S. Venkatraman, 2000. "A Permutation Test to Compare Receiver Operating Characteristic Curves," Biometrics, The International Biometric Society, vol. 56(4), pages 1134-1138, December.
    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. Strobl, Carolin & Boulesteix, Anne-Laure & Augustin, Thomas, 2007. "Unbiased split selection for classification trees based on the Gini Index," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 483-501, September.
    2. Alfo, Marco & Farcomeni, Alessio & Tardella, Luca, 2007. "Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5253-5265, July.

    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. Kubokawa, Tatsuya & Srivastava, Muni S., 2008. "Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1906-1928, October.
    2. Hossain, Ahmed & Beyene, Joseph & Willan, Andrew R. & Hu, Pingzhao, 2009. "A flexible approximate likelihood ratio test for detecting differential expression in microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3685-3695, August.
    3. Luca Scrucca, 2014. "Graphical tools for model-based mixture discriminant analysis," 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. 8(2), pages 147-165, June.
    4. Jin, Hua & Lu, Ying, 2009. "Permutation test for non-inferiority of the linear to the optimal combination of multiple tests," Statistics & Probability Letters, Elsevier, vol. 79(5), pages 664-669, March.
    5. Bilin Zeng & Xuerong Meggie Wen & Lixing Zhu, 2017. "A link-free sparse group variable selection method for single-index model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2388-2400, October.
    6. J. Burez & D. Van Den Poel, 2005. "CRM at a Pay-TV Company: Using Analytical Models to Reduce Customer Attrition by Targeted Marketing for Subscription Services," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/348, Ghent University, Faculty of Economics and Business Administration.
    7. Won, Joong-Ho & Lim, Johan & Yu, Donghyeon & Kim, Byung Soo & Kim, Kyunga, 2014. "Monotone false discovery rate," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 86-93.
    8. Jan, Budczies & Kosztyla, Daniel & von Törne, Christian & Stenzinger, Albrecht & Darb-Esfahani, Silvia & Dietel, Manfred & Denkert, Carsten, 2014. "cancerclass: An R Package for Development and Validation of Diagnostic Tests from High-Dimensional Molecular Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i01).
    9. Jianqing Fan & Yang Feng & Jiancheng Jiang & Xin Tong, 2016. "Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 275-287, March.
    10. Márton Gosztonyi & Csákné Filep Judit, 2022. "Profiling (Non-)Nascent Entrepreneurs in Hungary Based on Machine Learning Approaches," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    11. Wang, Tao & Xu, Pei-Rong & Zhu, Li-Xing, 2012. "Non-convex penalized estimation in high-dimensional models with single-index structure," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 221-235.
    12. Elisa–María Molanes-López & Ricardo Cao, 2008. "Relative density estimation for left truncated and right censored data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(8), pages 693-720.
    13. Un Jung Lee & ShengLi Tzeng & Yu-Chuan Chen & James J Chen, 2017. "Development of Predictive Signatures for Treatment Selection in Precision Medicine," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 2(4), pages 83-88, August.
    14. Alan R Dabney & John D Storey, 2007. "Optimality Driven Nearest Centroid Classification from Genomic Data," PLOS ONE, Public Library of Science, vol. 2(10), pages 1-7, October.
    15. Zhao, Jianhua & Yu, Philip L.H. & Shi, Lei & Li, Shulan, 2012. "Separable linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4290-4300.
    16. Chakraborty, Sounak, 2009. "Simultaneous cancer classification and gene selection with Bayesian nearest neighbor method: An integrated approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1462-1474, February.
    17. Shaheena Bashir & Edward Carter, 2010. "Penalized multinomial mixture logit model," Computational Statistics, Springer, vol. 25(1), pages 121-141, March.
    18. Park, Junyong & Park, DoHwan, 2015. "Stein’s method in high dimensional classification and applications," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 110-125.
    19. Chakraborty, Sounak, 2009. "Bayesian binary kernel probit model for microarray based cancer classification and gene selection," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4198-4209, October.
    20. Kasim Adetayo & Lin Dan & Van Sanden Suzy & Clevert Djork-Arné & Bijnens Luc & Göhlmann Hinrich & Amaratunga Dhammika & Hochreiter Sepp & Shkedy Ziv & Talloen Willem, 2010. "Informative or Noninformative Calls for Gene Expression: A Latent Variable Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-31, January.

    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:50:y:2006:i:3:p:783-802. 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.