Simple and effective boundary correction for kernel densities and regression with an application to the world income and Engel curve estimation

DOI10.1016/j.csda.2010.03.029zbMath1284.91444OpenAlexW1964295675MaRDI QIDQ2445704

Stefan Sperlich, Jing Dai

Publication date: 14 April 2014

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

Full work available at URL: https://archive-ouverte.unige.ch/unige:23359

zbMATH Keywords

kernel regressionboundary correctionkernel density estimationlocal bandwidth

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Density estimation (62G07) Statistical methods; economic indices and measures (91B82)

Related Items

Nonparametric kernel density estimation near the boundary ⋮ Model-free model-fitting and predictive distributions ⋮ Functional regression approximate Bayesian computation for Gaussian process density estimation ⋮ Mellin-Meijer kernel density estimation on \(\mathbb{R}^+\) ⋮ Probit transformation for kernel density estimation on the unit interval ⋮ On Modeling Wood Formation Using Parametric and Semiparametric Regressions for Count Data ⋮ An automatic clustering algorithm for probability density functions ⋮ Boundary estimation with the fuzzy set density estimator

Uses Software

• LOWESS

Cites Work

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• The World Income Distribution
• On Non-Parametric Estimates of Density Functions and Regression Curves
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