Bayesian computation for logistic regression

Computational Statistics and Data Analysis

Volumn 48, Issue 4, 2005, Pages 857-868

  Groenewald, Pieter C N ^a   Mokgatlhe, Lucky ^b  

^a UNIVERSITY OF THE FREE STATE   (South Africa)

^b UNIVERSITY OF BOTSWANA   (Botswana)

Author keywords

Bayes factors; Data augmentation; Gibbs sampling; Logit model; Ordinal data; Polychotomous response

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; COMPUTER SIMULATION; DATA REDUCTION; MATHEMATICAL MODELS; NORMAL DISTRIBUTION; PARAMETER ESTIMATION;

BAYES FACTORS; DATA AUGMENTATION; GIBBS SAMPLING; LOGIT MODELS; ORDINAL DATA; POLYCHOTOMOUS RESPONSE;

REGRESSION ANALYSIS;

EID: 10444227379     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2004.04.009     Document Type: Article

References (14)

1. Albert, J.H., Chib, S., 1993. Bayesian analysis of binary and polychotomous response data. J. Amer. Statist. Assoc. 88, 669-679.
2. Chib, S., 1995. Marginal likelihood from the Gibbs output. J. Amer. Statist. Assoc. 90, 1313-1321.
3. Cox, D.R., 1971. The Analysis of Binary Data. Methuen, London.
4. Fahrmeir, L., Tutz, G., 2001. Multivariate Statistical Modelling Based on Generalized Linear Models, 2nd Edition. Springer, New York.
5. Gelfand, A.E., Smith, A.P.M., 1990. Sampling-based approaches to calculating marginal densities. J. Amer. Statist. Assoc. 85, 398-409.
6. Griffiths, W.E., Hill, R.C., Pope, P.J., 1987. Small sample properties of probit model estimators. J. Amer. Statist. Assoc. 82, 929-937.
7. Hand, D.J., Daly, F., Lunn, A.D., McConway, K.J., Ostrowski, E., 1994. A Handbook of Small Data Sets. Chapman & Hall, London.
8. Hastings, W.K., 1970. Monte Carlo sampling methods using Markov chain and their applications. Biometrika 87, 97-109.
9. Kass, R.E., Raftery, A.E., 1995. Bayes factors. J. Amer. Statist. Assoc. 90, 773-795.
10. Maddala, O.S., 1983. Limited Dependent and Qualitative Variables in Econometrics. Cambridge University Press, New York.
11. Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., Teller, E., 1953. Equations of state calculations by fast computing machines. J. Chem. Phys. 21, 1087-1091.
12. Piegorsch, W.W., 1992. Complimentary log regression for generalized linear models. Amer. Statistician 46, 94-99.
13. Tanner, T.A., Wong, W.H., 1987. The calculation of posterior distributions by data augmentation. J. Amer. Statist. Assoc. 82, 528-549.
14. Zellner, A., Rossi, P.E., 1984. Bayesian analysis of dichotomous quantal response models. J. Econometrics 25, 365-393.