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A regression approach for estimating the center of symmetry

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  • Hsieh, Fushing

Abstract

The center of symmetry of a distribution function is estimated by a convenient generalized least squares (GLS) estimator, which is constructed from a regression setup based on the strong approximation of the empirical quantile process. This GLS estimator is shown to be semiparametric efficient in the sense of achieving the Fisher information bound. As a by-product, a [chi]2 test for the symmetry assumption is also derived.

Suggested Citation

  • Hsieh, Fushing, 1995. "A regression approach for estimating the center of symmetry," Statistics & Probability Letters, Elsevier, vol. 22(2), pages 157-160, February.
    • Handle: RePEc:eee:stapro:v:22:y:1995:i:2:p:157-160
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    References listed on IDEAS

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    1. Koul H. L. & Susarla V., 1983. "Adaptive Estimation In Linear Regression," Statistics & Risk Modeling, De Gruyter, vol. 1(4-5), pages 379-400, May.
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