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A graphical tool for selecting the number of slices and the dimension of the model in SIR and SAVE approaches

  • Benoît Liquet

    ()

  • Jérôme Saracco

    ()

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    No abstract is available for this item.

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    File URL: http://hdl.handle.net/10.1007/s00180-011-0241-9
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    Article provided by Springer in its journal Computational Statistics.

    Volume (Year): 27 (2012)
    Issue (Month): 1 (March)
    Pages: 103-125

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    Handle: RePEc:spr:compst:v:27:y:2012:i:1:p:103-125
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    1. Zhu, Lixing & Miao, Baiqi & Peng, Heng, 2006. "On Sliced Inverse Regression With High-Dimensional Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 630-643, June.
    2. Zhu, Li-Ping & Zhu, Li-Xing, 2007. "On kernel method for sliced average variance estimation," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 970-991, May.
    3. Aragon, Y. & Saracco, J., 1996. "Sliced Inverse Regression (SIR): An Appraisal of Small Sample Alternatives to Slicing," Papers 95.392, Toulouse - GREMAQ.
    4. Yingcun Xia & Howell Tong & W. K. Li & Li-Xing Zhu, 2002. "An adaptive estimation of dimension reduction space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 363-410.
    5. Zhu, Li-Xing & Ohtaki, Megu & Li, Yingxing, 2007. "On hybrid methods of inverse regression-based algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2621-2635, February.
    6. Luke A. Prendergast, 2007. "Implications of influence function analysis for sliced inverse regression and sliced average variance estimation," Biometrika, Biometrika Trust, vol. 94(3), pages 585-601.
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