Non And Semi-Parametric Estimation In Models With Unknown Smoothness
AbstractMany asymptotic results for kernel-based estimators were established under some smoothness assumption on density. For cases where smoothness assumptions that are used to derive unbiasedness or asymptotic rate may not hold we propose a combined estimator that could lead to the best available rate without knowledge of density smoothness. A Monte Carlo example confirms good performance of the combined estimator.
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Bibliographic InfoPaper provided by McGill University, Department of Economics in its series Departmental Working Papers with number 2006-15.
Length: 10 pages
Date of creation: Sep 2006
Date of revision:
Other versions of this item:
- Kotlyarova, Yulia & Zinde-Walsh, Victoria, 2006. "Non- and semi-parametric estimation in models with unknown smoothness," Economics Letters, Elsevier, vol. 93(3), pages 379-386, December.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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