Semiparametric multiple kernel estimators and model diagnostics for count regression functions

DOI10.1080/03610926.2019.1568488OpenAlexW2912168334WikidataQ128492605 ScholiaQ128492605MaRDI QIDQ5077412

Tristan Senga Kiessé, Smail Adjabi, Lamia Djerroud

Publication date: 18 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2019.1568488

zbMATH Keywords

cross-validationmodel diagnosticsdiscrete multivariate kernelsemiparametric count regression

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Local multiplicative bias correction for asymmetric kernel density estimators
• Consistency and asymptotic normality for discrete associated-kernel estimator
• On semiparametric regression for count explanatory variables
• Local quasi-likelihood with a parametric guide
• Semiparametric density estimation by local \(L_ 2\)-fitting.
• Nonparametric density estimation with a parametric start
• Bayesian approach to bandwidth selection for multivariate count regression function estimation by associated discrete kernel
• Effects of associated kernels in nonparametric multiple regressions
• A Class of Improved Parametrically Guided Nonparametric Regression Estimators
• Multivariate binary discrimination by the kernel method
• The Lyapounov Central Limit Theorem for Factorizable Arrays
• Parametrically Guided Non‐parametric Regression
• Discrete triangular distributions and non-parametric estimation for probability mass function
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