Reducing bias in nonparametric density estimation via bandwidth dependent kernels: L1 view

Mynbaev, Kairat and Martins-Filho, Carlos (2016): Reducing bias in nonparametric density estimation via bandwidth dependent kernels: L1 view. Forthcoming in: Statistics and Probability Letters , Vol. 123, (2017): pp. 17-22.

Abstract

We define a new bandwidth-dependent kernel density estimator that improves existing convergence rates for the bias, and preserves that of the variation, when the error is measured in L1. No additional assumptions are imposed to the extant literature.

• Item Type: MPRA Paper
• Language: English
• Keywords: Kernel density estimation, higher order kernels, bias reduction
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General

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