Influence diagnostics in Birnbaum–Saunders nonlinear regression models

DOI10.1080/02664761003692357OpenAlexW1995678703MaRDI QIDQ5124807

Alexandre G. Patriota, Artur J. Lemonte

Publication date: 30 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0904.4139

zbMATH Keywords

local influencelifetime datageneralized leverageinfluence diagnosticBirnbaum-Saunders distributionfatigue life distributionmaximum-likelihood estimation

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (17)

Bimodal Birnbaum–Saunders generalized autoregressive score model ⋮ Unnamed Item ⋮ Diagnostics for a class of survival regression models with heavy-tailed errors ⋮ Influence diagnostics and model validation for the generalized extreme-value nonlinear regression model ⋮ A log-linear regression model for the \(\beta\)-Birnbaum-Saunders distribution with censored data ⋮ Diagnostic procedures in Birnbaum-Saunders nonlinear regression models ⋮ Diagnostic analysis for heterogeneous log-Birnbaum-Saunders regression models ⋮ The sinh-normal/independent nonlinear regression model ⋮ Heteroscedastic log-exponentiated Weibull regression model ⋮ Zero-inflated Bell regression models for count data ⋮ Birnbaum‐Saunders distribution: A review of models, analysis, and applications ⋮ A new extended Birnbaum-Saunders regression model for lifetime modeling ⋮ Improved likelihood-based inference in Birnbaum-Saunders nonlinear regression models ⋮ Multivariate Birnbaum–Saunders regression model ⋮ Diagnostic tools in generalized Weibull linear regression models ⋮ Birnbaum–Saunders statistical modelling: a new approach ⋮ The log-odd log-logistic Weibull regression model: modelling, estimation, influence diagnostics and residual analysis

Uses Software

• R
• Ox

Cites Work

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