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Averaged Singular Integral Estimation as a Bias Reduction Technique

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  • Delgado, Miguel A.
  • Vidal-Sanz, Jose M.

Abstract

This paper proposes an averaged version of singular integral estimators, whose bias achieves higher rates of convergence under smoothing assumptions. We derive exact bias bounds, without imposing smoothing assumptions, which are a basis for deriving the rates of convergence under differentiability assumptions.

Suggested Citation

  • Delgado, Miguel A. & Vidal-Sanz, Jose M., 2002. "Averaged Singular Integral Estimation as a Bias Reduction Technique," Journal of Multivariate Analysis, Elsevier, vol. 80(1), pages 127-137, January.
    • Handle: RePEc:eee:jmvana:v:80:y:2002:i:1:p:127-137
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    References listed on IDEAS

    as
    1. P. M. Robinson, 1989. "Hypothesis Testing in Semiparametric and Nonparametric Models for Econometric Time Series," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 56(4), pages 511-534.
    2. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    3. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-1430, November.
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    Cited by:

    1. Jose Vidal-Sanz, 2009. "Automatic spectral density estimation for random fields on a lattice via bootstrap," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(1), pages 96-114, May.

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