Full bandwidth matrix selectors for gradient kernel density estimate

DOI10.1016/j.csda.2012.07.006zbMath1365.62127OpenAlexW2062152696MaRDI QIDQ2359493

Kamila Vopatová, Ivana Horová, Jan Koláček

Publication date: 29 June 2017

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2012.07.006

zbMATH Keywords

asymptotic mean integrated square errormultivariate kernel densityunconstrained bandwidth matrix

Mathematics Subject Classification ID

Density estimation (62G07) Estimation in multivariate analysis (62H12)

Related Items (6)

Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation ⋮ Bandwidth matrix selectors for kernel regression ⋮ Kernel estimation of regression function gradient ⋮ Data-driven density derivative estimation, with applications to nonparametric clustering and bump hunting ⋮ Direct Density Derivative Estimation ⋮ Exact risk improvement of bandwidth selectors for kernel density estimation with directional data

Uses Software

• KernSmooth
• pyuvdata
• SiZer

Cites Work

• The commutation matrix: Some properties and applications
• Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices
• Feature significance for multivariate kernel density estimation
• A simple root \(n\) bandwidth selector
• A comparative study of several smoothing methods in density estimation
• Convergence rates for unconstrained bandwidth matrix selectors in multivariate kernel density estimation
• Smoothing methods in statistics
• Multivariate plug-in bandwidth selection
• Contribution to the bandwidth choice for kernel density estimates
• Visualization and Bandwidth Matrix Choice
• Asymptotics for general multivariate kernel density derivative estimators
• Biased and Unbiased Cross-Validation in Density Estimation
• Bootstrap choice of the smoothing parameter in kernel density estimation
• Cross-Validation of Multivariate Densities
• SiZer for Exploration of Structures in Curves
• Bandwidth selectors for multivariate kernel density estimation
• Facts about the gaussian probability density function
• Cross-validation Bandwidth Matrices for Multivariate Kernel Density Estimation
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