A Bayesian Approach to Parameter Estimation in Binary Logit and Probit Models

Year 2008, Volume: 37 Issue: 2, 167 - 176, 01.02.2008

D. Tektas S. Günay

Keywords

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References

• Albert, J.H. and Chib, S. Bayesian Analysis of Binary and Polychotomous Response Data, Journal of the American Statistical Association 422, 669–679, 1993.
• Gelfand, A.E. and Smith, A.F.M. Sampling-Based Approaches to Calculating Marginal Densities, Journal of the American Statistical Association 85, 398–409, 1990.
• Geweke, J. Evaluating the Accuracy of Sampling Based Approaches to the calculation of Posterior Moments, in: (Bayesian Statistics 4, Oxford University Press, 1992), 169-194.
• Holmes, C.C. and Held, L. Bayesian Auxiliary Variable Models for Binary and Multinomial Regression, Bayesian Analysis 1, 145–168, 2006.
• Lesage, J.P. Applied Econometrics using MATLAB (e-book: http://www.spatialeconometrics.com, 1999).
• Raftery, A.E. and Lewis, S. How many iterations in the Gibbs Sampler?, in: (Bayesian Statistics 4, Oxford University Press, 1992), 763–773.
• Tanner, M.A. Tools for Statistical Inference (Springer-Verlag, NewYork, 1993).
• Tanner, M.A. and Wong, W.H. The Calculation of Posterior Distributions by Data Aug- mentation, Journal of the American Statistical Association 82, 528–550, 1987.
• Walsh, B. Markov Chain Monte Carlo and Gibbs Sampling, Lecture Notes for EBB, http://www.nitro.biosci.arizona.edu/courses/EEB596/handouts/Gibbs.pdf, 2002.