Kernel density estimators from quantized data

DOI10.1016/S0362-546X(97)00462-8zbMath1063.62534OpenAlexW2082632300MaRDI QIDQ4374250

Mirosław Pawlak, Ulrich Stadtmüller

Publication date: 1997

Published in: Nonlinear Analysis: Theory, Methods & Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0362-546x(97)00462-8

zbMATH Keywords

rate of convergencekernel estimatorsquantizationnonparametric estimationgeneralized binding

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

Cites Work

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• Smoothing by weighted averaging of rounded points
• Nonparametric regression analysis of longitudinal data
• On the accuracy of binned kernel density estimators
• A simple class of asymptotically optimal quantizers
• Optimal Grouping, Spacing, Stratification, and Piecewise Constant Approximation
• Asymptotic quantization error of continuous signals and the quantization dimension
• The Influence of Rounding Errors on Some Nonparametric Estimators of a Density and its Derivatives
• Nonparametric Statistical Data Modeling
• Nonparametric estimation of a class of smooth functions
• Designs for Regression Problems with Correlated Errors

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