Advanced Search
MyIDEAS: Login to save this article or follow this journal

Prediction by Supervised Principal Components

Contents:

Author Info

  • Bair, Eric
  • Hastie, Trevor
  • Paul, Debashis
  • Tibshirani, Robert
Registered author(s):

    Abstract

    No abstract is available for this item.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.ingentaconnect.com/content/asa/jasa/2006/00000101/00000473/art00016
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of the American Statistical Association.

    Volume (Year): 101 (2006)
    Issue (Month): (March)
    Pages: 119-137

    as in new window
    Handle: RePEc:bes:jnlasa:v:101:y:2006:p:119-137

    Contact details of provider:
    Web page: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main

    Order Information:
    Web: http://www.amstat.org/publications/index.html

    Related research

    Keywords:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

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

    Cited by:
    1. Cheng, Cheng, 2009. "Internal validation inferences of significant genomic features in genome-wide screening," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 788-800, January.
    2. Chen, Xi & Wang, Lily & Ishwaran, Hemant, 2010. "An integrative pathway-based clinical-genomic model for cancer survival prediction," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1313-1319, September.
    3. Heij, C., 2007. "Improved forecasting with leading indicators: the principal covariate index," Econometric Institute Research Papers EI 2007-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Peter Bickel & Bo Li & Alexandre Tsybakov & Sara Geer & Bin Yu & Teófilo Valdés & Carlos Rivero & Jianqing Fan & Aad Vaart, 2006. "Regularization in statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 15(2), pages 271-344, September.
    5. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
    6. van Wieringen, Wessel N. & Kun, David & Hampel, Regina & Boulesteix, Anne-Laure, 2009. "Survival prediction using gene expression data: A review and comparison," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1590-1603, March.
    7. Eric Hillebrand & Tae-Hwy Lee, 2012. "Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors," CREATES Research Papers 2012-18, School of Economics and Management, University of Aarhus.
    8. Koch, Inge & Naito, Kanta, 2010. "Prediction of multivariate responses with a selected number of principal components," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1791-1807, July.
    9. Travaglini, Guido, 2011. "Principal Components and Factor Analysis. A Comparative Study," MPRA Paper 35486, University Library of Munich, Germany.
    10. Anestis Antoniadis & Piotr Fryzlewicz & Frédérique Letué, 2010. "The Dantzig selector in Cox's proportional hazards model," LSE Research Online Documents on Economics 30992, London School of Economics and Political Science, LSE Library.
    11. Klaus Abberger, 2007. "Forecasting Quarter-on-Quarter Changes of German GDP with Monthly Business Tendency Survey Results," Ifo Working Paper Series Ifo Working Paper No. 40, Ifo Institute for Economic Research at the University of Munich.
    12. Cem Cakmakli & Dick van Dijk, 2010. "Getting the Most out of Macroeconomic Information for Predicting Stock Returns and Volatility," Tinbergen Institute Discussion Papers 10-115/4, Tinbergen Institute.
    13. Travaglini, Guido, 2010. "Supervised Principal Components and Factor Instrumental Variables. An Application to Violent CrimeTrends in the US, 1982-2005," MPRA Paper 22077, University Library of Munich, Germany.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:bes:jnlasa:v:101:y:2006:p:119-137. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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