Posterior analysis of lognormal regression models using the Gibbs sampler
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DOI: 10.1007/s00362-006-0372-1
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References listed on IDEAS
- W. R. Gilks & P. Wild, 1992. "Adaptive Rejection Sampling for Gibbs Sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(2), pages 337-348, June.
- Sylvia. Richardson & Peter J. Green, 1997. "On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(4), pages 731-792.
- David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
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Cited by:
- Christopher Withers & Saralees Nadarajah, 2012. "Unbiased estimates for a lognormal regression problem and a nonparametric alternative," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(2), pages 207-227, February.
- Enrico Fabrizi & Carlo Trivisano, 2016. "Bayesian Conditional Mean Estimation in Log-Normal Linear Regression Models with Finite Quadratic Expected Loss," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1064-1077, December.
- Rijji Sen & Rakesh Ranjan & S. K. Upadhyay, 2017. "A simple Bayes analysis of Weibull Based Accelerated Test model," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 505-511, January.
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Keywords
Lognormal regression model; Gibbs sampler; sampling-importance-resampling; predictive simulation; chi-square and Kolmogorov-Smirnov discrepancy measures; posterior and fractional Bayes factors;All these keywords.
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