Frontier estimation using kernel smoothing estimators with data transformation

DOI10.1016/J.JKSS.2014.07.005zbMath1304.62145OpenAlexW1972977426MaRDI QIDQ488593

Hohsuk Noh

Publication date: 26 January 2015

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2014.07.005

zbMATH Keywords

monotonicityconcavitylinear programmingbandwidth selectiontransformed dataconstrained kernel smoothing estimatorPriestly-Chao estimator

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Density estimation (62G07) Nonparametric estimation (62G05) Integer programming (90C10)

Related Items (3)

A New Mathematical Model for the Efficiency Calculation ⋮ Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis ⋮ ROBUSTIFIED EXPECTED MAXIMUM PRODUCTION FRONTIERS

Cites Work

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• Versions of Kernel-Type Regression Estimators
• On Estimation of Monotone and Concave Frontier Functions
• Hazard analysis. I
• On Non-Parametric Estimates of Density Functions and Regression Curves

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