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New regression model with four regression structures and computational aspects
Authors:Thiago G. Ramires  Gauss M. Cordeiro  Gilberto A. Paula  Niel Hens
Affiliation:1. Department of Exact Sciences, University of S?o Paulo, S?o Paulo, Brazil;2. Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-Biostat), University of Hasselt, Hasselt, Belgium;3. Department of Statistics, Federal University of Pernambuco, Recife, Brazil;4. Department of Statistics, Institute of Mathematics and Statistics, USP, S?o Paulo, Brazil;5. Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-Biostat), University of Hasselt, Hasselt, Belgium;6. Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerpen, Belgium
Abstract:
A new general class of exponentiated sinh Cauchy regression models for location, scale, and shape parameters is introduced and studied. It may be applied to censored data and used more effectively in survival analysis when compared with the usual models. For censored data, we employ a frequentist analysis for the parameters of the proposed model. Further, for different parameter settings, sample sizes, and censoring percentages, various simulations are performed. The extended regression model is very useful for the analysis of real data and could give more adequate fits than other special regression models.
Keywords:Diagnostics analysis  Exponentiated sinh Cauchy regression model  GAMLSS  Survival analysis
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