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Nonparametric regression with errors in variables and applications

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  • Ioannides, D. A.
  • Alevizos, P. D.

Abstract

In this paper we consider the problem of the nonparametric regression estimation, when measurement errors are involved in the explanatory variable. Using Pollard empirical process the uniform consistency with sharp rates is established for the nonparametric estimator. Applications in the Engel curve analysis are discussed.

Suggested Citation

  • Ioannides, D. A. & Alevizos, P. D., 1997. "Nonparametric regression with errors in variables and applications," Statistics & Probability Letters, Elsevier, vol. 32(1), pages 35-43, February.
  • Handle: RePEc:eee:stapro:v:32:y:1997:i:1:p:35-43
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    References listed on IDEAS

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    1. Masry, E., 1993. "Asymptotic Normality for Deconvolution Estimators of Multivariate Densities of Stationary Processes," Journal of Multivariate Analysis, Elsevier, vol. 44(1), pages 47-68, January.
    2. Fan, Jianqing & Masry, Elias, 1992. "Multivariate regression estimation with errors-in-variables: Asymptotic normality for mixing processes," Journal of Multivariate Analysis, Elsevier, vol. 43(2), pages 237-271, November.
    3. Masry, Elias, 1993. "Strong consistency and rates for deconvolution of multivariate densities of stationary processes," Stochastic Processes and their Applications, Elsevier, vol. 47(1), pages 53-74, August.
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    Cited by:

    1. Delaigle, Aurore & Fan, Jianqing & Carroll, Raymond J., 2009. "A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 348-359.
    2. Qin, Huai-Zhen & Feng, Shi-Yong, 2003. "Deconvolution kernel estimator for mean transformation with ordinary smooth error," Statistics & Probability Letters, Elsevier, vol. 61(4), pages 337-346, February.
    3. Comte, F. & Lacour, C. & Rozenholc, Y., 2010. "Adaptive estimation of the dynamics of a discrete time stochastic volatility model," Journal of Econometrics, Elsevier, vol. 154(1), pages 59-73, January.

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