Regression trees for analysis of count data with extra Poisson variation

DOI10.1016/j.csda.2004.06.011zbMath1430.62165OpenAlexW2016450654MaRDI QIDQ957258

Hongshik Ahn, James J. Chen, Yun-Hee Choi

Publication date: 26 November 2008

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

Full work available at URL: https://doi.org/10.1016/j.csda.2004.06.011

zbMATH Keywords

recursive partitioningquasi-likelihoodgeneralized linear modelcarcinogenicity

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (5)

Count regression trees ⋮ Model trees with topic model preprocessing: an approach for data journalism illustrated with the WikiLeaks Afghanistan war logs ⋮ Gaining insight with recursive partitioning of generalized linear models ⋮ Regression trees and forests for non-homogeneous Poisson processes ⋮ Accurate estimation for extra-Poisson variability assuming random effect models

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• Tree-Structured Logistic Model for Over-Dispersed Binomial Data with Application to Modeling Developmental Effects
• Fitting Mixed Poisson Regression Models Using Quasi‐Likelihood Methods
• Tree-Structured Proportional Hazards Regression Modeling

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