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Multivariate partially linear regression in the presence of measurement error

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  • Seçil Yalaz

    (Dicle University)

Abstract

In this paper, multivariate partially linear model with error in the explanatory variable of nonparametric part, where the response variable is m dimensional, is considered. By modification of local-likelihood method, an estimator of parametric part is driven. Moreover, the asymptotic normality of the generalized least square estimator of the parametric component is investigated when the error distribution function is either ordinarily smooth or super smooth. Applications in the Engel curves are discussed and through Monte Carlo experiments performances of $$\hat{\beta }_{n}$$ β ^ n are investigated.

Suggested Citation

  • Seçil Yalaz, 2019. "Multivariate partially linear regression in the presence of measurement error," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(1), pages 123-135, March.
  • Handle: RePEc:spr:alstar:v:103:y:2019:i:1:d:10.1007_s10182-018-0326-7
    DOI: 10.1007/s10182-018-0326-7
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    References listed on IDEAS

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    4. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
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