Partially Linear Expectile Regression Using Local Polynomial Fitting

Cécile Adam () and Irène Gijbels ()
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Cécile Adam: KU Leuven, Department of Mathematics
Irène Gijbels: Department of Mathematics and Leuven Statistics Research Center (LStat), KU Leuven

A chapter in Advances in Contemporary Statistics and Econometrics, 2021, pp 139-160 from Springer

Abstract: Abstract This chapter deals with partially linear expectile regression using local polynomial fitting as a basic smoothing technique in the various steps. The advantage of the estimation method is that an explicit expression for an optimal choice of the bandwidth (matrix) can be established, and based on this, a rule-of-thumb bandwidth selector is presented. A small simulation study demonstrates that the estimation method with this data-driven choice of the bandwidth performs very well. An illustration with a real data example is provided.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-73249-3_8

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DOI: 10.1007/978-3-030-73249-3_8

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