On a length-biased Birnbaum-Saunders regression model applied to meteorological data
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Publication:6096166
DOI10.1080/03610926.2022.2037642arXiv2012.10760OpenAlexW3114382383MaRDI QIDQ6096166
Unnamed Author, Roberto Vila, Unnamed Author, Helton Saulo
Publication date: 11 September 2023
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2012.10760
Cites Work
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- An adjusted boxplot for skewed distributions
- Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy
- A length-biased version of the Birnbaum-Saunders distribution with application in water quality
- Statistical inference for dependent stress-strength reliability of multi-state system using generalized survival signature
- A bivariate fatigue-life regression model and its application to fracture of metallic tools
- Inference of accelerated dependent competing risks model for Marshall-Olkin bivariate Weibull distribution with nonconstant parameters
- On the existence and uniqueness of the maximum likelihood estimates of parameters of Laplace Birnbaum-Saunders distribution based on type-I, type-II and hybrid censored samples
- Bathtub and Related Failure Rate Characterizations
- RELIABILITY ESTIMATION VIA LENGTH-BIASED TRANSFORMATION
- Birnbaum–Saunders statistical modelling: a new approach
- [Invited tutorial Birnbaum–Saunders regression models: a comparative evaluation of three approaches]
- On a log-symmetric quantile tobit model applied to female labor supply data
- Birnbaum‐Saunders distribution: A review of models, analysis, and applications
- Inference for the Birnbaum–Saunders Lifetime Regression Model with Applications
- A new family of life distributions
- A Log-Linear Model for the Birnbaum-Saunders Distribution
- Log‐symmetric quantile regression models
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