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Nonparametric variance function estimation with missing data

Author

Listed:
  • Pérez-González, A.
  • Vilar-Fernández, J.M.
  • González-Manteiga, W.

Abstract

In this paper, a fixed design regression model where the errors follow a strictly stationary process is considered. In this model the conditional mean function and the conditional variance function are unknown curves. Correlated errors when observations are missing in the response variable are assumed. Four nonparametric estimators of the conditional variance function based on local polynomial fitting are proposed. Expressions of the asymptotic bias and variance of these estimators are obtained. A simulation study illustrates the behavior of the proposed estimators.

Suggested Citation

  • Pérez-González, A. & Vilar-Fernández, J.M. & González-Manteiga, W., 2010. "Nonparametric variance function estimation with missing data," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1123-1142, May.
    • Handle: RePEc:eee:jmvana:v:101:y:2010:i:5:p:1123-1142
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    References listed on IDEAS

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