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Efficient estimation of population quantiles in general semiparametric regression models

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  • Maity, Arnab

Abstract

The problem of quantile estimation in general semiparametric regression models is considered. We derive plug-in kernel-based estimators, investigate their asymptotic distribution and establish the semiparametric efficiency of these estimators under mild assumptions. We apply our methodology in an example in nutritional epidemiology. The generalization to the important case where responses are missing at random is also addressed.

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  • Maity, Arnab, 2008. "Efficient estimation of population quantiles in general semiparametric regression models," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2744-2750, November.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:16:p:2744-2750
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    References listed on IDEAS

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    1. Xiaohong Chen & Oliver Linton & Ingrid Van Keilegom, 2003. "Estimation of Semiparametric Models when the Criterion Function Is Not Smooth," Econometrica, Econometric Society, vol. 71(5), pages 1591-1608, September.
    2. Maity, Arnab & Ma, Yanyuan & Carroll, Raymond J., 2007. "Efficient Estimation of Population-Level Summaries in General Semiparametric Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 123-139, March.
    3. Gerda Claeskens & Raymond J. Carroll, 2007. "An asymptotic theory for model selection inference in general semiparametric problems," Biometrika, Biometrika Trust, vol. 94(2), pages 249-265.
    4. Newey, Whitney K, 1990. "Semiparametric Efficiency Bounds," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(2), pages 99-135, April-Jun.
    5. Xihong Lin & Raymond J. Carroll, 2006. "Semiparametric estimation in general repeated measures problems," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(1), pages 69-88, February.
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