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Alan E. Gelfand, James B. Duke Emeritus Professor of Statistical Science and Professor Emeritus of Statistical Science and Professor in the Division of Environmental Sciences and Policy


Alan E. Gelfand

Contact Info:
Office Location:  223A Old Chem Bldg, Durham, NC 27708
Office Phone:  (919) 668-5229
Email Address: send me a message
Web Page:

Teaching (Fall 2018):

  • STA 944.01, SPATIAL STATISTICS Synopsis
    Old Chem 025, WF 11:45 AM-02:40 PM


Ph.D.Stanford University1969
M.S.Stanford University1967
B.S.City College of New York1965


Bayesian Statistics

Research Interests: Bayesian Models, Spatial Data Analysis, and Nonparametric Bayesian Methods


Adolescent • Adult • African Americans • Age Factors • Algorithms • Animals • Arsenic • Bayes Theorem • Biogeography • Biometry • Birth Certificates • Birth Order • Birth Weight • Cluster Analysis • Computer Simulation • Continental Population Groups • Cross-Sectional Studies • Data Collection • Data Interpretation, Statistical • Databases, Factual • Ecology • Ecosystem • Education • Environmental Monitoring • Ethnic Groups • European Continental Ancestry Group • Exotic plants • Female • Forecasting • Forestry • Fresh Water • Gaussian processes • Geographic Information Systems • Gestational Age • Health Status Disparities • Hispanic Americans • Humans • Hypertension • Hypertension, Pregnancy-Induced • Infant Mortality • Infant, Low Birth Weight • Infant, Newborn • Infant, Small for Gestational Age • Inference • Likelihood Functions • Linear Models • Logistic Models • Male • Marital Status • Markov Chains • Maternal Age • Maternal Exposure • Models, Biological • Models, Chemical • Models, Statistical • Models, Theoretical • Monte Carlo Method • Mothers • Multivariate Analysis • North Carolina • Odds Ratio • Particulate Matter • Plant Transpiration • Plants • Poisson Distribution • Population • Poverty • Pregnancy • Pregnancy Complications, Cardiovascular • Pregnancy Outcome • Premature Birth • Racism • Regression Analysis • Residence Characteristics • Risk Assessment • Risk Factors • Seedling • Smoking • Statistical Distributions • Time Factors • Trees • Vernalization • Young Adult

Curriculum Vitae

Current Ph.D. Students  
  • Graduate Students  

Representative Publications   (More Publications)   (search)

  1. A.E. Gelfand (with P. Diggle, M. Fuentes, P. Guttorp), The Handbook of Spatial Statistics. (2009), Chapman Hall (forthcoming)
  2. A. Gelfand with Carlin, B.P., Mugglin, A.S., and Zhu, L., Modeling spatio-temporally misaligned areal and point process environmental data, in Quantitative Methods for Current Environmental Issues, edited by C. Anderson, et. al. (2002), pp. 3-35, London, Springer Verlag
  3. A.E. Gelfand (with Clark, J.S.), Hierarchical Modeling for Environmental Data; Some applications and Perspectives. (2006), Oxford University Press.
  4. A. Gelfand, Bayesian Computation, in Encyclopedia of Environmetrics, edited by A.H. El-Shaarawi and W.W. Piegorsch, vol. 1 (2002), pp. 150-151
  5. A.E. Gelfand (with S. Banerjee and B.P. Carlin), Hierarchical Modeling and Analysis for Spatial Data (2004), Chapman Hall, Boca Raton.
  6. A. Gelfand, Bayesian Methods and Modeling, in Encyclopedia of Environmetrics, edited by A.H. El-Shaarawi and W.W. Piegorsch, vol. 1 (2002), pp. 155-160
  7. A. Gelfand with M. Haran, B.P. Carlin, J.L. Adgate, G. Ramachandran and L.A. Waller, Hierarchical models for relating particulant matter exposure measures, in Case Studies in Bayesian Statistics, edited by C. Gatsonis, et. al., vol. VI (2002), pp. 239-254, New York, Springer-Verlag
  8. A. Gelfand, Gibbs Sampling, in Statistics in the 21st Century, edited by A.E. Raftery, M.A. Tanner, M.T. Wells (2001), pp. 341-349, Chapman Hall/CRC, Boca Raton
  9. A. Gelfand, Gibbs Sampling, in Statistics in the 21st Century, edited by A.E. Raftery, M.A. Tanner, M.T. Wells (2001), pp. 341-349, Chapman Hall/CRC, Boca Raton
  10. A. Gelfand with M. Ghosh, Generalized Linear Models: A Bayesian View, in Generalized Linear Models: A Bayesian Perspective, edited by D.K. Dey, M. Ghosh and S. Ghosh (2000), pp. 3-22, Marcel Dekker Press
  11. A. Gelfand with N. Ravishanker and M.D. Ecker, Modeling and Inference for Binary Spatial Data, in Generalized Linear Models: A Bayesian Perspective, edited by D.K. Dey, M. Ghosh and S. Ghosh (2000), pp. 373-386, Marcel Dekker Press
  12. Latimer, AM; Wu, S; Gelfand, AE; Silander, JA, Building statistical models to analyze species distributions., Ecological Applications : a Publication of the Ecological Society of America, vol. 16 no. 1 (February, 2006), pp. 33-50, ISSN 1051-0761 [doi]  [abs]
  13. Gelfand, AE; Kottas, A; MacEachern, SN, Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing, Journal of the American Statistical Association, vol. 100 no. 471 (2005), pp. 1021-1035, ISSN 0162-1459 [doi]  [abs]
  14. Gelfand, AE; Short, M; Carlin, BP, Covariate-adjusted Spatial CDF's for Air Pollutant Data, Journal of Agricultural, biological and environmental Statistics no. 10 (2005), pp. 259-275
  15. Gelfand, AE; Agarwal, D; Silander, J; Mickelson, J; Dewar, R, Relating Tropical Deforestation and Population Pressure through spatially Explicit Misaligned Bivariate Regression Models, Ecological Modelling no. 185 (2005), pp. 105-131
  16. Gelfand, AE; Valenti, J; Wu, S; Sirmans, CF, Apartment Rent Predictions Using Spatial Modeling, Journal of Real Estate Research no. 27 (2005), pp. 1, 105-136
  17. Agarwal, DK; Gelfand, AE, Slice sampling for simulation based fitting of spatial data models, Statistics and Computing, vol. 15 no. 1 (2005), pp. 61-69 [doi]  [abs]
  18. Gelfand, AE; Banerjee, S; Gamerman, D, Spatial Process Modelling for Univariate and Multivariate Dynamic spatial Data, Environmetrics, vol. 16 no. 16 (2005), pp. 1-15 [doi]  [abs]
  19. Gelfand, AE; Schmidt, AM; Wu, S; Silander, JA; Latimer, A; Rebelo, AG, Explaining Species diversity Through species Level Hierarchical Modeling., Applied Statistics no. 65 (2005), pp. 1-20
  20. Gelfand, AE; Silander Jr, JA; Wu, S; Latimer, A; Lewis, PO; Rebelo, AG; Holder, M, Explaining Species Distribution Patterns Through Hierarchical Modeling, Bayesian Analysis, vol. 1 no. 1 (2005), pp. 1; 41-92, ISSN 1936-0975 [doi]  [abs]
  21. Majumdar, A; Gelfand, AE; Banerjee, S, Spatio-temporal change-point modeling, Journal of Statistical Planning and Inference, vol. 130 no. 1-2 (2004), pp. 149-166 [doi]  [abs]
  22. Gelfand, AE; Ecker, MD; Knight, JR; Sirmans, CF, The Dynamics of Location in Home Price, Journal of Real Estate Finance and Economics, vol. 29 no. 2 (2004), pp. 149-166, ISSN 0895-5638 [doi]  [abs]
  23. Gelfand, AE; Schmidt, AM; Banerjee, S; Sirmans, CF, Nonstationary Multivariate Process Modelling through Spatially Varying Coregionalization (with discussion), Test no. 13 (2004), pp. 2; 1-50
  24. Gelfand, AE, Discussion to: Statistical Research: Some Advice for Beginners, The American Statistician no. 58 (2004), pp. 197-199
  25. Latimer, AM; Jr, JAS; Gelfand, AE; Rebelo, AG; Richardson, DM, Quantifying threats to biodiversity from invasive alien plants and other factors: A case study from the Cape Floristic Region, South African Journal of Science, vol. 100 no. 1-2 (2004), pp. 81-86  [abs]
  26. Gelfand, AE; Banerjee, S; Knight, JR; Sirmans, CF, Nonstationary Spatial Modeling through Normalized Distance-Weighted Sums of Stationary Processes, Journal of Business and Economic Statistics no. 22 (2004), pp. 206-213
  27. Gelfand, AE; Kim, H-J; Sirmans, CF; Banerjee, S, Spatial Modeling With Spatially Varying Coefficient Processes, Journal of the American Statistical Association, vol. 98 no. 462 (2003), pp. 387-396 [doi]  [abs]
  28. Gelfand, AE; Vounatsou, P, Proper multivariate conditional autoregressive models for spatial data analysis., Biostatistics (Oxford, England), vol. 4 no. 1 (January, 2003), pp. 11-25 [doi]  [abs]
  29. Gelfand, A.E., Some Comments on Model Criticism, in Highly Structured Stochastic Systems, edited by P.J. Green, N.L. Hjort and S. Richardson (2003), pp. 449-453, Oxford University Press, Oxford
  30. Gelfand, A.E., P. Vlachos, On the Calibration of Bayesian Model Choice Criteria, Journal of Satistical Planning and Inference, vol. 111 (2003), pp. 223-234
  31. Trevisani, M; Gelfand, AE, Inequalities between expected marginal log-likelihoods, with implications for likelihood-based model complexity and comparison measures, Canadian Journal of Statistics, vol. 31 no. 3 (2003), pp. 239-250  [abs]
  32. Gelfand, AE; Kottas, A, Bayesian Semiparametric Regression for Median Residual Life, Scandinavian Journal of Statistics, vol. 30 no. 4 (2003), pp. 651-665  [abs]
  33. Banerjee, S; Gelfand, AE; Sirmans, CF, Directional Rates of Change under Spatial Process Models, Journal of the American Statistical Association, vol. 98 no. 464 (2003), pp. 946-954, ISSN 0162-1459 [doi]  [abs]
  34. Zhu, L; Carlin, BP; Gelfand, AE, Hierarchical regression with misaligned spatial data: Relating ambient ozone and pediatric asthma ER visits in Atlanta, Environmetrics, vol. 14 no. 5 (2003), pp. 537-557 [doi]  [abs]
  35. Gelfand, AE; Fu, R; Holsinger, K, Exact Moment Calculations for Genetic Models, Journal of Theoretical Population Biology no. 63 (2003), pp. 231-243
  36. Banerjee, S; Gelfand, AE, On smoothness properties of spatial processes, Journal of Multivariate Analysis, vol. 84 no. 1 (2003), pp. 85-100 [doi]  [abs]
  37. Gelfand, AE; Schmidt, AM, A Bayesian Coregionalization Approach for Multivariate Pollutant Data, Journal of Geophysical Research, vol. Atmosphere no. 108 (2003), pp. D24, 8783  [abs]
  38. Vounatsou, P; Smith, T; Gelfand, AE, Spatial modelling of gene frequencies in the presence of undetectable alleles, Journal of Applied Statistics, vol. 30 no. 1 (2003), pp. 49-62 [doi]  [abs]
  39. Gelfand, AE; Ecker, MD, Spatial Modeling and Prediction Under Range Anisotropy, Environmental and Ecological Statistics no. 10 (2003), pp. 165-178
  40. Vlachos, PK; Gelfand, AE, On the calibration of Bayesian model choice criteria, Journal of Statistical Planning and Inference, vol. 111 no. 1-2 (2003), pp. 223-234, ISSN 0378-3758 [doi]  [abs]
  41. Wang, F; Gelfand, AE, A Simulation-based Approach to Bayesian Sample Size Determination for Performance under a Given Model and for Separating Models, Statistical Science, vol. 17 no. 2 (May, 2002), pp. 193-208 [doi]  [abs]
  42. Gelfand, A; Kottas, A, A Computational Approach for Full Nonparametric Bayesian Inference in Single and Multiple Sample Problems, Journal of Computational and Graphical Statistics, vol. 114 (2002), pp. 289-305
  43. Gelfand, AE; Carlin, CP; Mugglin, AS; Zhu, L, Modeling spatiotemporally misaligned areal and point process environmental data., Quantitative Methods for Current Environmental Issues, vol. 1 (2002), pp. 150-151
  44. Sfiridis, J; Gelfand, A, A survey of sampling-based Bayesian analysis of financial data, Applied Mathematical Finance, vol. 9 no. 4 (2002), pp. 273-291  [abs]
  45. Gelfand, AE; Clapp, JM; Kim, H-J, Spatial Prediction of House Prices Using LPR and Bayesian Smoothing, Real Estate Economics, vol. 30 (2002)
  46. Kottas, A; Branco, MD; Gelfand, AE, A nonparametric Bayesian modeling approach for cytogenetic dosimetry, Biometrics, vol. 58 no. 3 (2002), pp. 593-600, ISSN 0006-341X  [abs]
  47. Gelfand, A; Agarwal, D; Pousty, S, Zero-inflated regression models for spatial count data, Environmental and Ecological Statistics (2002)
  48. Gelfand, A; Banerjee, S, Prediction, interpolation and regression for spatially misaligned data points, Sankhya A, vol. 64 (2002), pp. 227-245
  49. Agarwal, DK; Gelfand, AE; Jr, JAS, Investigating tropical deforestation using two-stage spatially misaligned regression models, Journal of Agricultural, Biological, and Environmental Statistics, vol. 7 no. 3 (2002), pp. 420-439 [doi]  [abs]
  50. Gelfand, A; Trevisani, M, Discussion to "Bayesian measures of model complexity and fit, J. Royal Statistical Soc., vol. B (2002), pp. 631
  51. Gelfand, A; Zhu, L; Carlin, BP, On the Change of Support Problem for Spatio-Temporal Data, Biostatistics, vol. 20 (2001), pp. 31-45
  52. Gelfand, AE; Carlin, BP; Trevisani, M, On computation using Gibbs sampling for multilevel models, Statistica Sinica, vol. 11 no. 4 (2001), pp. 981-1003  [abs]
  53. Gelfand, AE; Kottas, A, Nonparametric Bayesian modeling for stochastic order, Annals of the Institute of Statistical Mathematics, vol. 53 no. 4 (2001), pp. 865-876 [doi]  [abs]
  54. Gelfand, A; Kottas, A, Modeling Variability Order: A Semiparametric Bayesian Approach, Methodology and Computing In Applied Probability, vol. 31 (2001), pp. 427-442
  55. Kottas, A; Gelfand, AE, Bayesian Semiparametric Median Regression Modeling, Journal of the American Statistical Association, vol. 96 no. 456 (2001), pp. 1458-1468, ISSN 0162-1459  [abs]
  56. Gelfand, A; Carlin, BP; Zhu, L, Accommodating Scale Misalignment In Spatio-Temporal Data In: Bayesian Methods with Applications to Science, Policy and Official Statistics (2001), pp. 81-90
  57. Gelfand, A; Ghosh, SK; Christiansen, C; Soumerai, SB; McLaughlin, TJ, Proportional Hazards Models: A Latent Risks Approach, Applied Statistics, vol. 49 (2000), pp. 385-397
  58. Christiansen, CL; Wang, F; Barton, MB; Kreuter, W; Elmore, JG; Gelfand, AE; Fletcher, SW, Predicting the cumulative risk of false-positive mammograms, Journal of the National Cancer Institute, vol. 92 no. 20 (2000), pp. 1657-1666, ISSN 0027-8874  [abs]
  59. Gelfand, AE; Wang, F, Modelling the cumulative risk for a false-positive under repeated screening events, Statistics in Medicine, vol. 19 no. 14 (2000), pp. 1865-1879 [doi]  [abs]
  60. Gelfand, A; Mugglin, A; Carlin, BP, Fully Model Based Approaches for Misaligned Spatial Data, Journal American Statistical Association, vol. 95 no. 451 (2000), pp. 877-887, ISSN 0162-1459  [abs]
  61. Gelfand, A; Vounatsou, P; Smith, T, Modeling of Multinominal data with latent structure: application to geographical mapping of human gene and haplotype frequencies, Biostatistics, vol. 10 (2000), pp. 177-189
  62. Gelfand, AE, Gibbs Sampling, Journal of the American Statistical Association, vol. 95 no. 452 (2000), pp. 1300-1304, ISSN 0162-1459 (Reprinted in Statistics In the 21st Century, Edited by A.E. Raftery, M.A. Tanner and M.T. Wells, Chapman and Hall/CRC 2001, 341-350.)
  63. Banerjee, S; Gelfand, AE; Polasek, W, Geostatistical modelling for spatial interaction data with application to postal service performance, Journal of Statistical Planning and Inference, vol. 90 no. 1 (2000), pp. 87-105  [abs]
  64. Gelfand, A, Discussion to Bayesian Backfitting, Statistical Science, vol. 15 no. 3 (2000), pp. 217-218
  65. Gelfand, A; Ecker, MD; Christiansen, C; Soumerai, SB; McLaughlin, TJ, Conditional Categorical Response Models with Application to Treatment Compliance for and Survival of AMI Patients, Applied Statistics, vol. 49 (2000), pp. 171-186
  66. Gelfand, A; Sahu, S, Gibbs Sampling, Identifiability and Improper Priors in Generalized Linear Mixed Models, Journal American Statistical Association, vol. 94 no. 445 (1999), pp. 247-253, ISSN 0162-1459  [abs]
  67. Carlin, BP; Kadane, JB; Gelfand, AE, Approaches for optimal sequential decision analysis in clinical trials., Biometrics, vol. 54 no. 3 (1998), pp. 964-975, ISSN 0006-341X [doi]  [abs]
  68. Gelfand, A, Model choice: a minimum posterior predictive loss approach, Biometrika, vol. 85 no. 1 (1998), pp. 1-11, ISSN 0006-3444 [doi]  [abs]
  69. Gelfand, AE; Dey, D; Swartz, T; Vlachos, P, Simulation Based Model Checking for Hierarchical Models, Test, vol. 7 no. 2 (1998), pp. 325-346  [abs]
  70. Gelfand, AE; Ecker, MD, Modeling and Inference for Geometrically Anisotropic Spatial Data, Mathematical Geology, vol. 31 (1998), pp. 67-83
  71. Gelfand, AE; Ghosh, SK, Latent Waiting Time Models for Bivariate Event Times with Censoring, Sankhya B, vol. 60 (1998), pp. 31-47
  72. Knight, JR; Sirmans, CF; Gelfand, AE; Ghosh, SK, Analyzing real estate data problems using the Gibbs sampler, Real Estate Economics, vol. 26 no. 3 (1998), pp. 469-492  [abs]
  73. Gelfand, AE; Ghosh, SK, A Latent Risk Approach for Modeling Individual Level Data Consisting of Multiple Event Times, Journal of Statistical Research, vol. 32 (1998), pp. 23-39
  74. Gelfand, AE; Ghosh, SK; Knight, JR; Sirmans, CF, Spatio-temporal modeling of residential sales data, Journal of Business and Economic Statistics, vol. 16 no. 3 (1998), pp. 312-321  [abs]
  75. Dey, DK; Gelfand, AE; Peng, F, Overdispersed generalized linear models, Journal of Statistical Planning and Inference, vol. 64 no. 1 (1997), pp. 93-107  [abs]
  76. Ecker, MD; Gelfand, AE, Bayesian Variogram Modeling for an Isotropic Spatial Process, Journal of Agricultural, Biological, and Environmental Statistics, vol. 2 no. 4 (1997), pp. 347-369  [abs]
  77. Gelfand, AE; Mallick, BK; Polasek, W, Broken biological size relationships: A truncated semiparametric regression approach with measurement error, Journal of the American Statistical Association, vol. 92 no. 439 (1997), pp. 836-845  [abs]
  78. Waller, LA; Carlin, BP; Xia, H; Gelfand, AE, Hierarchical spatio-temporal mapping of disease rates, Journal of the American Statistical Association, vol. 92 no. 438 (1997), pp. 607-617  [abs]
  79. Mukhopadhyay, S; Gelfand, AE, Dirichlet process mixed generalized linear models, Journal of the American Statistical Association, vol. 92 no. 438 (1997), pp. 633-639  [abs]
  80. Gelfand, AE; Vlachos, P, Issues in Bayesian Clinical Trial Design for Categorical Endpoint Models, Proceedings of the Biometrics Section (1996), ASA Meeting
  81. Gelfand, AE; Sfiridis, J, Bayesian Analysis of Financial Event Study Data, Advances in Econometrics, vol. 11 (1996), pp. 25-62
  82. Mallick, BK; Gelfand, AE, Semiparametric errors-in-variables models: A Bayesian approach, Journal of Statistical Planning and Inference, vol. 52 no. 3 (1996), pp. 307-321 [doi]  [abs]
  83. Gelfand, AE, Discussion to Empirical methods for combining likelihoods, J. Amer. Statist. Assoc., vol. 91 no. 434 (1996), pp. 551-552 [doi]
  84. Gelfand, AE; Mukhopadhyay, S, On Nonparametric Bayesian Inference for the Distribution of a Random Sample, Canadian Journal of Statistics, vol. 23 (1995), pp. 411-420
  85. Gelfand, AE; Sahu, SK; Carlin, BP, Efficient parametrisations for normal linear mixed models, Biometrika, vol. 82 no. 3 (1995), pp. 479-488, ISSN 0006-3444 [doi]  [abs]
  86. Gelfand, AE; Carlin, BP, Comment on Bayesian Computation and Stochastic Systems, Statistical Science, vol. 10 no. 1 (1995), pp. 43-46 [doi]
  87. Gelfand, AE; Mallick, B, Bayesian analysis of semiparametric proportional hazards models, Biometrics, vol. 51 no. 3 (1995), pp. 843-852, ISSN 0006-341X [doi]  [abs]
  88. Geland, AE; Mallic, B; Dey, D, Modeling expert opinion: likelihoods under incomplete probabilistic specification, J. Amer Statist. Assoc., vol. 90 no. 430 (1995), pp. 598-604 [doi]
  89. Gelfand, AE; Sahu, S, On Markov chain Monte Carlo acceleration, Journal of Computational and Graphical Statistics, vol. 3 (1995), pp. 261-276
  90. Gelfand, AE; Mallick, B, Discussion to Assessment and Propagation of Model Uncertainty, J. Royal Stat. Soc. B, vol. 57 (1995), pp. 82-83
  91. Gelfand, AE; Pai, J; Ravishanker, N, Bayesian analysis of concurrent time series with application to regional IBM revenue data, Journal of Forecasting, vol. 13 (1994), pp. 463-479
  92. MALLICK, BK; GELFAND, AE, Generalized linear models with unknown link functions, Biometrika, vol. 81 no. 2 (1994), pp. 237-245, ISSN 0006-3444 [doi]  [abs]
  93. Gelfand, AE; Dey, D, Bayesian model choice: asymptotic and exact calculations, Journal Royal Statistical Society B, vol. 56 (1994), pp. 501-514
  94. Carlin, BP; Gelfand, AE, Parametric likelihood inference for record breaking problems, Biometrika, vol. 80 no. 3 (1993), pp. 507-515, ISSN 0006-3444 [doi]  [abs]
  95. Gelfand, AE; Carlin, B, Meximum likelihood estimation for constrained or missing data models, Canadian Journal of Statistics, vol. 21 no. 3 (1993), pp. 303-311 [doi]
  96. Gelfand, AE, Discussion to Approximate Bayesian Inference with the Weighted Likelihood Bootstrap, J. Royal Statistical Society B, vol. 56 (1993), pp. 36-37
  97. Gelfand, AE; Racine Poon, A; Smith, AFM; Wakefield, J, Bayesian analysis of population models using the Gibbs sampler, Applied Statistics, vol. 43 (1993), pp. 201-221
  98. Gelfand, AE, Discussion to "Inference from Iterative Simulation using Multiple Sequences" and "Practical Markov Chain Monte Carlo", Statistical Science, vol. 7 (1993), pp. 486-487
  99. Gelfand, AE, Discussion to the papers of Smith and Roberts, Besag and Green, and Gilks et al., J. Royal Statistical Society B, vol. 55 (1993), pp. 70-71
  100. Gelfand, AE; Glaz, J; Kuo, L; Lee, T-M, Inference for the maximum cell probability under multinomial sampling, Naval Research Logistics, vol. 39 no. 1 (1992), pp. 97-114 [doi]
  101. Gelfand, AE, Discussion to Constrained Monte Carlo maximum likelihood for dependent data, Journal Royal Statistical Society B, vol. 54 (1992), pp. 690-691
  102. Gelfand, AE; Lange, N; Carlin, B, Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4+ counts (with discussion), Journal Amer. Stat. Assoc., vol. 87 (1992), pp. 615-632 (JASA applications paper of the year.)
  103. Gelfand, AE; Smith, AFM; Lee, T-M, Bayesian analysis of constrained parameter and truncated data problems, Journal Amer. Stat. Assoc., vol. 87 no. 418 (1992), pp. 523-532 [doi]
  104. Gelfand, AE; Smith, AFM, Bayesian statistics without tears: a sampling-resampling perspective, American Statistician, vol. 46 (1992), pp. 84-88
  105. Gelfand, AE; Crabtree, B; Zyzanski, S; Miller, WL; O'Connor, PJ; Winsemius, D, Data analysis in primary care research: log linear models, Family Medicine, vol. 24 no. 2 (1992), pp. 145-151  [abs]
  106. Gelfand, AE; Carlin, B; Smith, AFM, Hierarchical Bayesian analysis of change point problems, Applied Statistics, vol. 41 (1992), pp. 389-405
  107. Wakefield, JC; Gelfand, AE; Smith, AFM, Efficient generation of random variates via the ratio-of-uniforms method, Statistics and Computing, vol. 1 no. 2 (1992), pp. 129-133, ISSN 0960-3174 [doi]  [abs]
  108. Carlin, BP; Gelfand, AE, An iterative Monte Carlo method for nonconjugate Bayesian analysis, Statistics and Computing, vol. 1 no. 2 (1991), pp. 119-128, ISSN 0960-3174 [doi]  [abs]
  109. Gelfand, AE; Kuo, L, Nonparametric Bayesian bioassay including ordered polytomous response, Biometrika, vol. 78 no. 3 (1991), pp. 657-666, ISSN 0006-3444 [doi]  [abs]
  110. Gelfand, AE; Smith, AFM, Gibbs sampling for marginal posterior expectations, Communications in Statistics, Theory and Methods, vol. 20 no. 5 and 6 (1991), pp. 1747-1766 [doi]
  111. Gelfand, AE; Dey, DK, On measuring Bayesian robustness of contaminated classes of priors, Statistics and Decisions, vol. 9 (1990), pp. 63-80
  112. Gelfand, AE; Carlin, B, A Sample Reuse Method for Accurate Parametric Empirical Bayes Confidence Intervals, Journal Royal Stat. Soc. Ser. B, vol. 53 (1990), pp. 189-200
  113. GELFAND, A, Illustration of Bayesian inference in normal data models using Gibbs sampling., J. An. Stat. Assoc., vol. 85 no. 412 (1990), pp. 972-985 [doi]
  114. GELFAND, A, Sampling Based Approaches to Calculating Marginal Densities, Journal of the American Statistical Association, vol. 85 no. 410 (1990), pp. 398-409 (Reprinted in "Breakthroughs in Statistics".) [doi]
  115. Gelfand, AE; Carlin, B, Approaches for Empirical Bayes Confidence Intervals, Journal Amer. Stat. Assoc., vol. 85 (1990), pp. 105-114
  116. Gelfand, AE; Dalal, SR, A note on overdispersed exponential families, Biometrika, vol. 77 no. 1 (1990), pp. 55-64, ISSN 0006-3444 [doi]  [abs]
  117. Dey, DK; Gelfand, AE, Improved estimation of a patterned covariance matrix, Journal of Multivariate Analysis, vol. 31 no. 1 (1990), pp. 107-116, ISSN 0047-259X  [abs]