Reparameterized Birnbaum-Saunders regression models with varying precision
By Manoel Santos-Neto, Francisco José de A. Cysneiros, Víctor Leiva, Michelli Barros. 2016
60 citations recorded by the source corpus.
We propose a methodology based on a reparameterized Birnbaum-Saunders regression model with varying precision, which generalizes the existing works in the literature on the topic. This methodology includes the estimation of model parameters, hypothesis tests for the precision parameter, a residual analysis and influence diagnostic tools. Simulation studies are conducted to evaluate its performance. We apply it to two real-world case-studies to show its potential with the R software. MSC 2010 subject classifications: Primary 62J12, 62J20; secondary 62F03.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/e74955df0a653c2718093544014dde98aa4f02a8
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In Statistics and Probability
- Debasis Kundu
- Narayanaswamy Balakrishnan
- Biswabrata Pradhan
- Gauss Moutinho Cordeiro
- Rameshwar D. Gupta
- Saralees Nadarajah
- Sanku Dey
- Edwin M. M. Ortega
Citations in the corpus
- Birnbaum‐Saunders distribution: A review of models, analysis, and applications (2018, background): “[236] proposed a reparameterized BS regression model with varying precision and discussed associated inferential issues.”