On Modeling Wood Formation Using Parametric and Semiparametric Regressions for Count Data

DOI10.1080/03610918.2013.875570zbMath1346.62148OpenAlexW2019253978MaRDI QIDQ2816704

Henri E. Cuny, Tristan Senga Kiessé

Publication date: 25 August 2016

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2013.875570

zbMATH Keywords

count regression functiondiscrete kernelbootstrap resampling methodsgeneralized linear and additive modelsoptimal bandwidth selectionswood formation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to environmental and related topics (62P12) Nonparametric estimation (62G05) Point estimation (62F10)

Related Items

Bayesian estimation of bandwidth in semiparametric kernel estimation of unknown probability mass and regression functions of count data

Uses Software

• lme4
• mgcv
• gamm4

Cites Work

• Unnamed Item
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• Simple and effective boundary correction for kernel densities and regression with an application to the world income and Engel curve estimation
• Binomial kernel and Bayes local bandwidth in discrete function estimation
• Bayesian Approach in Nonparametric Count Regression with Binomial Kernel
• Generalized Additive Models for Location, Scale and Shape