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Estimators in step regression models

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  • Müller, Ursula U.
  • Schick, Anton
  • Wefelmeyer, Wolfgang

Abstract

We consider nonparametric regression models in which the regression function is a step function, and construct a convolution estimator for the response density that has the same bias as the usual estimators based on the responses, but a smaller asymptotic variance.

Suggested Citation

  • Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2015. "Estimators in step regression models," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 124-129.
    • Handle: RePEc:eee:stapro:v:100:y:2015:i:c:p:124-129
    DOI: 10.1016/j.spl.2015.02.012
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    References listed on IDEAS

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