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An analysis of single-index model with monotonic link function

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Abstract

The single-index model with monotonic link function is investigated. Firstly, it is showed that the link function h(·) can be viewed by a graphic method. That is, the plot with the fitted response ŷ on the horizontal axis and the observed y on the vertical axis can be used to visualize the link function. It is pointed out that this graphic approach is also applicable even when the link function is not monotonic. Note that many existing nonparametric smoothers can also be used to assess h(·). Therefore, the I-spline approximation of the link function via maximizing the covariance function with a penalty function is investigated in the present work. The consistency of the criterion is constructed. A small simulation is carried out to evidence the efficiency of the approach proposed in the paper.

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References

  1. Li K C, Duan N H. Regression analysis under link violation, Ann Statist, 1989, 17: 1009–1052.

    Article  MATH  MathSciNet  Google Scholar 

  2. Duan N H, Li K C. Slicing regression: a link-free regression method, Ann Statist, 1991, 19:502–530.

    Article  MathSciNet  Google Scholar 

  3. Härdle W, Hall P, Ichimura H. Optimal smoothing in single-index models, Ann Statist, 1993, 21:157–178.

    Article  MATH  MathSciNet  Google Scholar 

  4. Ichimura H. Semi-parametric least squares (SLS) and weighted SLS estimation of single-index models, J Econometrics, 1993, 58: 71–120.

    Article  MATH  MathSciNet  Google Scholar 

  5. Hristache M, Juditsky A, Spokoiny V. Direct estimation of the index coefficients in a single-index model, Ann Statist, 2001, 29: 595–623.

    Article  MATH  MathSciNet  Google Scholar 

  6. Härdle W, Stoker T M. Investigating smooth multiple regression by the method of average derivatives, J Amer Statist Assoc, 1989, 84: 986–995.

    Article  MATH  MathSciNet  Google Scholar 

  7. Cook R D, Weisberg S. Transforming a response variable for linearity, Biometrika, 1994, 81:731–737.

    Article  MATH  Google Scholar 

  8. Eaton M L. A characterization of spherical distributions, J Multi Analysis, 1986, 20: 272–276.

    Article  MATH  MathSciNet  Google Scholar 

  9. Eubank R L. Nonparametric Regression and Spline Smoothing, New York: Marcel Dekker, 1999.

    MATH  Google Scholar 

  10. Ramsay J O. Monotone regression spline in action(with discussion), Statist Sci, 1988, 3: 425–461.

    Article  Google Scholar 

  11. Schwarz G. Estimating the dimension of a model, Ann Statist, 1978, 6: 461–464.

    Article  MATH  MathSciNet  Google Scholar 

  12. Zhu L X, Zhu L P, Li X. Transformed partial least squares for multivariate data, Statistica Sinica, 2007, 17: 1657–1675.

    MathSciNet  Google Scholar 

  13. Fujikoshi Y, Satoh K. Modified AIC and C p in multivariate linear regression, Biometrika, 1997, 84: 707–716.

    Article  MATH  MathSciNet  Google Scholar 

  14. McQuarri A D R, Trai C L. Regression and Time Series Model Selection, Singapore: World Scientific, 1998.

    Google Scholar 

Download references

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Supported by the National Natural Science Foundation of China (10701035), ChenGuang Project of Shanghai Education Development Foundation (2007CG33), and a Special Fund for Young Teachers in Shanghai Universities (79001320).

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Zhu, Lp., Yang, Xy., Yu, Z. et al. An analysis of single-index model with monotonic link function. Appl. Math. J. Chin. Univ. 23, 107–112 (2008). https://doi.org/10.1007/s11766-008-0115-2

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  • DOI: https://doi.org/10.1007/s11766-008-0115-2

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