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Variance estimation for high-dimensional regression models

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  • Spokoiny, Vladimir G.

Abstract

The paper is concerned with the problem of variance estimation for a high-dimensional regression model. The results show that the accuracy n -1/2 of variance estimation can be achieved only under some restrictions on smoothness properties of the regression function and on the dimensionality of the model. In particular, for a two times differentiable regression function, the rate n-1/2 is achievable only for dimensionality smaller or equal to 8. For higher dimensional model, the optimal accuracy is n-4jd which is worse than n-1/2 . The rate optimal estimating procedure is presented.

Suggested Citation

  • Spokoiny, Vladimir G., 1999. "Variance estimation for high-dimensional regression models," SFB 373 Discussion Papers 1999,86, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:199986
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    Cited by:

    1. Hardle W. & Sperlich S. & Spokoiny V., 2001. "Structural Tests in Additive Regression," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1333-1347, December.

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