References
- Bates , D. M. and Watts , D. G. 1988 . Nonlinear Regression Analysis and Its Applications , New York : John Wiley .
- Besag , J. 1974 . Spatial Interaction and the Statistical Analysis of Lattice Systems . Journal of the Royal Statistical Society , 36 : 192 – 326 . (with discussion), Ser. B
- Carlin , B. P. and Gelfand , A. E. 1991 . An Iterative Monte Carlo Method for Nonconjugate Bayesian Analysis . Statistics and Computing , 1 : 119 – 128 .
- Carlin , B. P. , Gelfand , A. E. and Smith , A. F. M. 1991 . Hierarchical Bayesian Analysis of Change Point Problems . Journal of the Royal Statistical Society , 41 : 389 – 405 . Ser. C.
- Carlin , B. P. and Poison , N. G. 1991 . Inference for Nonconjugate Bayesian Models Using the Gibbs Sampler . Canadian Journal of Statistics , 19 : 399 – 405 .
- Gelfand , A. E. , Hills , S. E. , Racine-Poon , A. and Smith , A. F. M. 1990 . Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling . Journal of the American Statistical Association , 85 : 972 – 985 .
- Gelfand , A. E. and Smith , A. F. M. 1990 . Sampling-Based Approaches to Calculating Marginal Densities . Journal of the American Statistical Association , 85 : 398 – 409 .
- Gelfand , A. E. and Smith , A. F. M. 1991 . Gibbs Sampling for Marginal Posterior Expectations . Communications in Statistics, Part A—Theories and Methods , 20 : 1747 – 1766 .
- Gelfand , A. E. , Smith , A. F. M. and Lee , T. M. 1992 . Bayesian Analysis of Constrained Parameter and Truncated Data Problems Using Gibbs Sampling . Journal of the American Statistical Association , 87 : 523 – 532 .
- Geman , S. and Geman , D. 1984 . Stochastic Relaxation, Gibbs Distributions and the Bayesian Restoration of Images . IEEE Transactions on Pattern Analysis and Machine Intelligence , 6 : 721 – 741 .
- Gilks , W. R. and Wild , P. 1992 . Adaptive Rejection Sampling for Gibbs Sampling . Journal of the Royal Statistical Society , 41 : 337 – 348 . Ser. C
- Glasser , M. 1965 . Regression Analysis With Dependent Variable Censored . Biometrics , 21 : 300 – 307 .
- Hastings , W. K. 1970 . Monte Carlo Sampling Methods Using Markov Chains and Their Applications . Biometrika , 57 : 97 – 109 .
- Lawless , J. F. 1982 . Statistical Models and Methods for Lifetime Data , New York : John Wiley .
- Li , K. H. 1988 . Imputation Using Markov Chains . Journal of Statistical Computation and Simulation , 30 : 57 – 79 .
- Liu , J. , Wong , W. H. and Kong , A. 1991a . Correlation Structure and Convergence Rate of the Gibbs Sampler (I): Applications to the Comparison of Estimators and Augmentation Schemes , University of Chicago, Dept. of Statistics . Technical Report
- Liu , J. , Wong , W. H. and Kong , A. 1991b . Correlation Structure and Convergence Rate of the Gibbs Sampler (II): Applications to Various Scans , University of Chicago, Dept. of Statistics . Technical Report
- Marske , D. 1967 . Biomedical Oxygen Demand Data Interpretation Using Sums of Squares Surface , University of Wisconsin . unpublished master's thesis
- Metropolis , N. , Rosenbluth , A. W. , Rosenbluth , M. N. , Teller , A. H. and Teller , E. 1953 . Equation of State Calculations by Fast Computing Machines . Journal of Chemical Physics , 21 : 1087 – 1092 .
- Rao , C. R. 1973 . Linear Statistical Inference , New York : John Wiley .
- Schervish , M. J. and Carlin , B. P. 1990 . On the Convergence of Successive Substitution Sampling , Carnegie Mellon University, Dept. of Statistics . Technical Report
- Tanner , M. A. and Wong , W. H. 1987 . The Calculation of Posterior Distributions by Data Augmentation . Journal of the American Statistical Association , 82 : 528 – 550 . (with discussion)
- Verdinelli , I. and Wasserman , L. 1991 . Bayesian Analysis of Outlier Problems Using the Gibbs Sampler . Statistics and Computing , 1 : 105 – 117 .
- Wei , G. C. G. and Tanner , M. A. 1990 . Posterior Computations with Censored Regression Data . Journal of the American Statistical Association , 85 : 829 – 839 .
- Zeger , S. and Karim , M. R. 1991 . Generalized Linear Models with Random Effects: A Gibbs Sampling Approach . Journal of the American Statistical Association , 86 : 79 – 86 .