Simulating comparisons of different computing algorithms fitting zero-inflated Poisson models for zero abundant counts

DOI10.1080/00949655.2017.1327590OpenAlexW2620379988MaRDI QIDQ5106959

Bryan Winter, Li Tang, Xueyan Liu, Bo Zhang, Hui Zhang, Zhiwei Zhang

Publication date: 22 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2017.1327590

zbMATH Keywords

nonlinear optimizationcount dataoverdispersionzero-inflated Poissonexcess zeroeszeroinfl

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• SAS
• pscl
• PROC GENMOD
• SAS/STAT

Cites Work

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• Comparison of some conjugate direction procedures for function minimization
• Variable Metric Method for Minimization
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• Restart procedures for the conjugate gradient method
• Function minimization by conjugate gradients
• Microeconometrics
• A Family of Variable-Metric Methods Derived by Variational Means
• A new approach to variable metric algorithms
• The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
• Conditioning of Quasi-Newton Methods for Function Minimization
• A Simplex Method for Function Minimization

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