A family of kernels and their associated deconvolving kernels for normally distributed measurement errors

DOI10.1080/00949655.2014.928712zbMath1457.62101OpenAlexW1968981664MaRDI QIDQ5220869

B. Lütkenöner

Publication date: 27 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2014.928712

zbMATH Keywords

kernel density estimationdensity deconvolutionFaddeeva functiondeconvolving kernel

Mathematics Subject Classification ID

Density estimation (62G07)

Uses Software

• KernSmooth
• decon
• Algorithm 916

Cites Work

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• Practical bandwidth selection in deconvolution kernel density estimation
• Exact and asymptotically optimal bandwidths for kernel estimation of density functionals
• Bandwidth selection: Classical or plug-in?
• Estimating smooth distribution function in the presence of heteroscedastic measurement errors
• Combinatorial sums and finite differences
• The effects of error magnitude and bandwidth selection for deconvolution with unknown error distribution
• Algorithm 916
• Deconvolving kernel density estimators
• Deconvolution with supersmooth distributions
• A Review of Some Non-parametric Methods of Density Estimation
• Data-driven deconvolution
• Computation of the Complex Error Function
• More efficient computation of the complex error function

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