A new semiparametric Weibull cure rate model: fitting different behaviors within GAMLSS

DOI10.1080/02664763.2019.1611748OpenAlexW2942743272MaRDI QIDQ5036914

Gauss M. Cordeiro, Josmar Mazucheli, Rodrigo R. Pescim, Ana Julia Righetto, Thiago G. Ramires, Luiz R. Nakamura

Publication date: 25 February 2022

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

Full work available at URL: https://doi.org/10.1080/02664763.2019.1611748

zbMATH Keywords

regression modelsresidual analysisP-splinelong-term survivorssmoothing functions

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• GAMLSS

Cites Work

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• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• A New Bayesian Model for Survival Data with a Surviving Fraction
• Gaussian Markov random field spatial models in GAMLSS
• Flexible Cure Rate Modeling Under Latent Activation Schemes
• Generalized Linear Models with Random Effects
• Generalized Additive Models for Location, Scale and Shape
• Bayesian survival analysis

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