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Multivariate partially linear models

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  • Pateiro-López, Beatriz
  • González-Manteiga, Wenceslao

Abstract

Univariate partially linear regression models have been widely discussed in recent years. In this paper, we consider a multivariate partially linear regression model under independent errors, where the response variable is d-dimensional. We obtain the asymptotic bias and variance for both the parametric and the nonparametric components. Moreover, we investigate the asymptotic normality of the LS estimator of the parametric component.

Suggested Citation

  • Pateiro-López, Beatriz & González-Manteiga, Wenceslao, 2006. "Multivariate partially linear models," Statistics & Probability Letters, Elsevier, vol. 76(14), pages 1543-1549, August.
  • Handle: RePEc:eee:stapro:v:76:y:2006:i:14:p:1543-1549
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    References listed on IDEAS

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    1. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    2. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
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    Cited by:

    1. Atak, Alev & Linton, Oliver & Xiao, Zhijie, 2011. "A semiparametric panel model for unbalanced data with application to climate change in the United Kingdom," Journal of Econometrics, Elsevier, vol. 164(1), pages 92-115, September.
    2. Przystalski, Marcin, 2014. "Estimation of the covariance matrix in multivariate partially linear models," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 380-385.

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