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Sliced Inverse Regression (SIR): An Appraisal of Small Sample Alternatives to Slicing

Author

Listed:
  • Aragon, Y.
  • Saracco, J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Aragon, Y. & Saracco, J., 1996. "Sliced Inverse Regression (SIR): An Appraisal of Small Sample Alternatives to Slicing," Papers 95.392, Toulouse - GREMAQ.
    • Handle: RePEc:fth:gremaq:95.392
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    Citations

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    Cited by:

    1. Coudret, R. & Girard, S. & Saracco, J., 2014. "A new sliced inverse regression method for multivariate response," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 285-299.
    2. Ali Gannoun & Jérôme Saracco, 2003. "Two Cross Validation Criteria for SIR α and PSIR α methods in view of prediction," Computational Statistics, Springer, vol. 18(3), pages 585-603, September.
    3. Benoît Liquet & Jérôme Saracco, 2012. "A graphical tool for selecting the number of slices and the dimension of the model in SIR and SAVE approaches," Computational Statistics, Springer, vol. 27(1), pages 103-125, March.

    More about this item

    Keywords

    ECONOMETRICS; EVALUATION; MATHEMATICS;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other

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