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New efficient spline estimation for varying-coefficient models with two-step knot number selection

Author

Listed:
  • Jun Jin

    (Southwestern University of Finance and Economics)

  • Tiefeng Ma

    (Southwestern University of Finance and Economics)

  • Jiajia Dai

    (Guizhou University)

Abstract

One of the advantages for the varying-coefficient model is to allow the coefficients to vary as smooth functions of other variables and the coefficients functions can be estimated easily through a simple B-spline approximations method. This leads to a simple one-step estimation procedure. We show that such a one-step method cannot be optimal when some coefficient functions possess different degrees of smoothness. Under the regularity conditions, the consistency and asymptotic normality of the two step B-spline estimators are also derived. A few simulation studies show that the gain by the two-step procedure can be quite substantial. The methodology is illustrated by an AIDS data set.

Suggested Citation

  • Jun Jin & Tiefeng Ma & Jiajia Dai, 2021. "New efficient spline estimation for varying-coefficient models with two-step knot number selection," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 693-712, July.
    • Handle: RePEc:spr:metrik:v:84:y:2021:i:5:d:10.1007_s00184-020-00798-8
    DOI: 10.1007/s00184-020-00798-8
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    References listed on IDEAS

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