Asymmetric Kernel Density Estimation Based on Grouped Data with Applications to Loss Model

DOI10.1080/03610918.2012.712184zbMath1291.62088OpenAlexW1998787058MaRDI QIDQ5415877

Sun Xu

Publication date: 19 May 2014

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.712184

zbMATH Keywords

grouped dataasymmetric kernelloss model

Mathematics Subject Classification ID

Density estimation (62G07)

Related Items (5)

From grouped to de-grouped data: a new approach in distribution fitting for grouped data ⋮ Tuning parameter-free nonparametric density estimation from tabulated summary data ⋮ Density deconvolution from grouped data with additive errors ⋮ Asymptotic properties of Dirichlet kernel density estimators ⋮ EM algorithm for mixture of skew-normal distributions fitted to grouped data

Cites Work

• Beta kernel estimators for density functions
• Local multiplicative bias correction for asymmetric kernel density estimators
• The tight constant in the Dvoretzky-Kiefer-Wolfowitz inequality
• Density estimation for grouped data with application to line transect sampling
• Locally parametric nonparametric density estimation
• Kernel density estimation of actuarial loss functions
• Incorporating support constraints into nonparametric estimators of densities
• Bootstrap choice of the smoothing parameter in kernel density estimation
• CONSISTENCY OF ASYMMETRIC KERNEL DENSITY ESTIMATORS AND SMOOTHED HISTOGRAMS WITH APPLICATION TO INCOME DATA
• Density estimation using inverse and reciprocal inverse Gaussian kernels
• All of Nonparametric Statistics
• A Useful Convergence Theorem for Probability Distributions
• Probability density function estimation using gamma kernels

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