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Corpus ID: 88523437

Sufficient Conditions for a Linear Estimator to be a Local Polynomial Regression

@article{Sidorenko2018SufficientCF,
title={Sufficient Conditions for a Linear Estimator to be a Local Polynomial Regression},
author={Alexander Sidorenko and Kurt S. Riedel},
journal={arXiv: Methodology},
year={2018}
}

It is shown that any linear estimator that satisfies the moment conditions up to order $p$ is equivalent to a local polynomial regression of order $p$ with some non-negative weight function if and only if the kernel has at most $p$ sign changes. If the data points are placed symmetrically about the estimation point, a linear weighting function is equivalent to the standard quadratic weighting function.

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