Data sharpening via Firth's adjusted score function

DOI10.1016/j.spl.2020.108831zbMath1450.62023OpenAlexW3030572588MaRDI QIDQ2197603

Yanyan Li

Publication date: 1 September 2020

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2020.108831

zbMATH Keywords

derivative estimationlocal likelihooddata perturbationadjusted score function

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Point estimation (62F10) Generalized linear models (logistic models) (62J12)

Uses Software

• KernSmooth
• sharpData

Cites Work

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• Local likelihood density estimation
• Data sharpening methods for bias reduction in nonparametric regression.
• Nonparametric kernel regression subject to monotonicity constraints
• Local Likelihood Estimation
• An Effective Bandwidth Selector for Local Least Squares Regression
• Local Regression and Likelihood
• Bias reduction of maximum likelihood estimates
• Miscellanea. Data sharpening as a prelude to density estimation
• Making a Non-Parametric Density Estimator More Attractive, and More Accurate, by Data Perturbation

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