17 Bayesian Generalized Linear Models

Sourish Das

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Reference

  1. Beayesian Data Analysis”, 3rd Edition, By Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari and Donald B. Rubin.
  2. Bayesian Statistics: An Introduction”, By Peter Lee, 4th Edition, ISBN: 978-1-118-33257-3.
  3. Monte Carlo Statistical Methods, By Robert, Christian P. andGeorge Casella. 2004. , 2nd edition. Springer.
  4. MCMCpack: Markov Chain Monte Carlo in R.”, (2011), Andrew D. Martin, Kevin M. Quinn, and Jong HeePark,Journal of Statistical Software. 42(9): 1-21.
  5. Applied Bayesian Modeling” By Peter Congdon, 2nd Edition,Wiley,. ISBN: 978-1-119-95151-3
  6. Bayes Linear Statistics, Theory Methods”. By Goldstein,Michael; Woo, David (2007). Wiley. ISBN978-0-470-01562-9.
  7. Hosmer, D.W. and Lemeshow, S. (1989) Applied LogisticRegression. New York: Wiley.
  8. Venables, W. N. and Ripley, B. D. (2002) Modern AppliedStatistics with S. Fourth edition. Springer.
  9. Albert, J. H. and S. Chib. 1993. \Bayesian Analysis of Binaryand Polychotomous Response Data.”J. Amer. Statist. Assoc.88, 669-679.
  10. Albert, J. H. and S. Chib. 1995. \Bayesian Residual Analysisfor Binary Response Regression Models.” Biometrika. 82,747-759.
  11. Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park.2011. “MCMCpack: Markov Chain Monte Carlo in R.”,Journal of Statistical Software. 42(9): 1-21.http://www.jstatsoft.org/v42/i09/I
  12. Siddhartha Chib. 1995. \Marginal Likelihood from the GibbsOutput.”Journal of the American Statistical Association.90:1313-1321.
  13. Peter E. Rossi, Greg M. Allenby and Rob McCulloch, Bayesian Statistics and Marketing (2005), Wiley-Interscience, New York, NY.
  14. Adelino F. da Silva, cudaBayesreg: Bayesian Computation inCUDA (2010), The R Journal, Vol. 2/2, 48-55.http://journal.r-project.org/archive/2010-2/RJournal_2010-2_FerreiradaSilva.pdf