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Publications of Alan E. Gelfand    :chronological  alphabetical  combined  bibtex listing:

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Books

  1. A.E. Gelfand (with P. Diggle, M. Fuentes, P. Guttorp), The Handbook of Spatial Statistics. (2009), Chapman Hall (forthcoming)
  2. A.E. Gelfand (with Clark, J.S.), Hierarchical Modeling for Environmental Data; Some applications and Perspectives. (2006), Oxford University Press.
  3. A.E. Gelfand (with S. Banerjee and B.P. Carlin), Hierarchical Modeling and Analysis for Spatial Data (2004), Chapman Hall, Boca Raton.

Papers Published

  1. Tang, B; Frye, HA; Gelfand, AE; Silander, JA, Zero-Inflated Beta Distribution Regression Modeling, Journal of Agricultural, Biological, and Environmental Statistics, vol. 28 no. 1 (March, 2023), pp. 117-137 [doi]  [abs]
  2. Tang, B; Clark, JS; Marra, PP; Gelfand, AE, Modeling Community Dynamics Through Environmental Effects, Species Interactions and Movement, Journal of Agricultural, Biological, and Environmental Statistics, vol. 28 no. 1 (March, 2023), pp. 178-195 [doi]  [abs]
  3. Hewitt, J; Gelfand, AE; Schick, RS, TIME-DISCRETIZATION APPROXIMATION ENRICHES CONTINUOUS-TIME DISCRETE-SPACE MODELS FOR ANIMAL MOVEMENT, The Annals of Applied Statistics, vol. 17 no. 1 (March, 2023), pp. 740-760 [doi]  [abs]
  4. Hewitt, J; Gelfand, AE; Quick, NJ; Cioffi, WR; Southall, BL; DeRuiter, SL; Schick, RS, Kernel density estimation of conditional distributions to detect responses in satellite tag data, Animal Biotelemetry, vol. 10 no. 1 (December, 2022) [doi]  [abs]
  5. Shirota, S; Gelfand, AE, Preferential sampling for bivariate spatial data, Spatial Statistics, vol. 51 (October, 2022) [doi]  [abs]
  6. Cebrián, AC; Asín, J; Gelfand, AE; Schliep, EM; Castillo-Mateo, J; Beamonte, MA; Abaurrea, J, Spatio-temporal analysis of the extent of an extreme heat event, Stochastic Environmental Research and Risk Assessment : Research Journal, vol. 36 no. 9 (September, 2022), pp. 2737-2751 [doi]  [abs]
  7. Castillo-Mateo, J; Lafuente, M; Asín, J; Cebrián, AC; Gelfand, AE; Abaurrea, J, Spatial Modeling of Day-Within-Year Temperature Time Series: An Examination of Daily Maximum Temperatures in Aragón, Spain, Journal of Agricultural, Biological, and Environmental Statistics, vol. 27 no. 3 (September, 2022), pp. 487-505 [doi]  [abs]
  8. White, PA; Frye, H; Christensen, MF; Gelfand, AE; Silander, JA, SPATIAL FUNCTIONAL DATA MODELING OF PLANT REFLECTANCES, The Annals of Applied Statistics, vol. 16 no. 3 (September, 2022), pp. 1919-1936 [doi]  [abs]
  9. Gelfand, AE, Spatial modeling for the distribution of species in plant communities, Spatial Statistics, vol. 50 (August, 2022) [doi]  [abs]
  10. Vihrs, N; Møller, J; Gelfand, AE, Approximate Bayesian inference for a spatial point process model exhibiting regularity and random aggregation, Scandinavian Journal of Statistics, vol. 49 no. 1 (March, 2022), pp. 185-210 [doi]  [abs]
  11. Bravo, MA; Leong, MC; Gelfand, AE; Miranda, ML, Assessing Disparity Using Measures of Racial and Educational Isolation., International Journal of Environmental Research and Public Health, vol. 18 no. 17 (September, 2021), pp. 9384 [doi]  [abs]
  12. White, PA; Gelfand, AE, Multivariate functional data modeling with time-varying clustering, Test, vol. 30 no. 3 (September, 2021), pp. 586-602 [doi]  [abs]
  13. Tang, B; Clark, JS; Gelfand, AE, Modeling spatially biased citizen science effort through the eBird database, Environmental and Ecological Statistics, vol. 28 no. 3 (September, 2021), pp. 609-630 [doi]  [abs]
  14. White, PA; Gelfand, AE, Generalized Evolutionary Point Processes: Model Specifications and Model Comparison, Methodology and Computing in Applied Probability, vol. 23 no. 3 (September, 2021), pp. 1001-1021 [doi]  [abs]
  15. Schliep, EM; Gelfand, AE; Abaurrea, J; Asín, J; Beamonte, MA; Cebrián, AC, Long-term spatial modelling for characteristics of extreme heat events, Journal of the Royal Statistical Society: Series a (Statistics in Society), vol. 184 no. 3 (July, 2021), pp. 1070-1092 [doi]  [abs]
  16. Hewitt, J; Schick, RS; Gelfand, AE, Continuous-Time Discrete-State Modeling for Deep Whale Dives, Journal of Agricultural, Biological, and Environmental Statistics, vol. 26 no. 2 (June, 2021), pp. 180-199 [doi]  [abs]
  17. Gelfand, AE; Shirota, S, The role of odds ratios in joint species distribution modeling, Environmental and Ecological Statistics, vol. 28 no. 2 (June, 2021), pp. 287-302 [doi]  [abs]
  18. Hellmayr, C; Gelfand, AE, A Partition Dirichlet Process Model for Functional Data Analysis, Sankhya B, vol. 83 no. 1 (May, 2021), pp. 30-65 [doi]  [abs]
  19. Shirota, S; Gelfand, AE; Mateu, J, Analyzing car thefts and recoveries with connections to modeling origin–destination point patterns, Spatial Statistics, vol. 38 (August, 2020) [doi]  [abs]
  20. Gelfand, AE, Introduction to the special issue on frontiers in spatial research, Spatial Statistics, vol. 37 (June, 2020) [doi]
  21. Gelfand, AE, Statistical challenges in spatial analysis of plant ecology data, Spatial Statistics, vol. 37 (June, 2020) [doi]  [abs]
  22. Paci, L; Gelfand, AE; Beamonte, MA; Gargallo, P; Salvador, M, Spatial hedonic modelling adjusted for preferential sampling, Journal of the Royal Statistical Society: Series a (Statistics in Society), vol. 183 no. 1 (January, 2020), pp. 169-192 [doi]  [abs]
  23. Gelfand, AE; Shirota, S, Preferential sampling for presence/absence data and for fusion of presence/absence data with presence-only data, Ecological Monographs, vol. 89 no. 3 (August, 2019) [doi]  [abs]
  24. Shen, Y; Gelfand, AE, Exploring geometric anisotropy for point-referenced spatial data, Spatial Statistics, vol. 32 (August, 2019) [doi]  [abs]
  25. Wang, F; Wang, J; Gelfand, AE; Li, F, Disease Mapping With Generative Models, The American Statistician, vol. 73 no. 3 (July, 2019), pp. 213-223, Informa UK Limited [doi]  [abs]
  26. White, PA; Gelfand, AE; Rodrigues, ER; Tzintzun, G, Pollution state modelling for Mexico City, Journal of the Royal Statistical Society: Series a (Statistics in Society), vol. 182 no. 3 (June, 2019), pp. 1039-1060 [doi]  [abs]
  27. Schliep, EM; Gelfand, AE, Velocities for spatio-temporal point patterns, Spatial Statistics, vol. 29 (March, 2019), pp. 204-225, Elsevier BV [doi]  [abs]
  28. Shirota, S; Gelfand, AE; Banerjee, S, Spatial Joint Species Distribution Modeling using Dirichlet Processes., Statistica Sinica, vol. 29 no. 3 (January, 2019), pp. 1127-1154 [doi]  [abs]
  29. Wang, F; Bhattacharya, A; Gelfand, AE, Rejoinder on: Process modeling for slope and aspect with application to elevation data maps, Test, vol. 27 no. 4 (December, 2018), pp. 783-786, Springer Nature America, Inc [doi]
  30. Wang, F; Bhattacharya, A; Gelfand, AE, Process modeling for slope and aspect with application to elevation data maps, Test, vol. 27 no. 4 (December, 2018), pp. 749-772 [doi]  [abs]
  31. Lu, X; Gelfand, AE; Holland, DM, Local real-time forecasting of ozone exposure using temperature data, Environmetrics, vol. 29 no. 7 (November, 2018), pp. e2509-e2509, WILEY [doi]  [abs]
  32. Schliep, EM; Gelfand, AE; Clark, JS; Kays, R, Joint Temporal Point Pattern Models for Proximate Species Occurrence in a Fixed Area Using Camera Trap Data, Journal of Agricultural, Biological, and Environmental Statistics, vol. 23 no. 3 (September, 2018), pp. 334-357, Springer Nature America, Inc [doi]  [abs]
  33. Ahn, S; Chertkov, M; Gelfand, AE; Park, S; Shin, J, Maximum weight matching using odd-sized cycles: Max-product belief propagation and half-integrality, Ieee Transactions on Information Theory, vol. 64 no. 3 (March, 2018), pp. 1471-1480, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  34. Schliep, EM; Gelfand, AE; Mitchell, RM; Aiello-Lammens, ME; Silander, JA, Assessing the joint behaviour of species traits as filtered by environment, Methods in Ecology and Evolution, vol. 9 no. 3 (March, 2018), pp. 716-727, WILEY [doi]  [abs]
  35. Schliep, EM; Gelfand, AE; Holland, DM, Alternating Gaussian Process Modulated Renewal Processes for Modeling Threshold Exceedances and Durations., Stochastic Environmental Research and Risk Assessment : Research Journal, vol. 32 no. 2 (February, 2018), pp. 401-417 [doi]  [abs]
  36. Caponera, A; Denti, F; Rigon, T; Sottosanti, A; Gelfand, A, Hierarchical spatio-temporal modeling of resting state fMRI data, Springer Proceedings in Mathematics and Statistics, vol. 257 (January, 2018), pp. 111-130, ISBN 9783030000387 [doi]  [abs]
  37. Wang, F; Wang, J; Gelfand, A; Li, F, Accommodating the ecological fallacy in disease mapping in the absence of individual exposures., Statistics in Medicine, vol. 36 no. 30 (December, 2017), pp. 4930-4942 [doi]  [abs]
  38. White, P; Gelfand, AE; Utlaut, T, Prediction and Model Comparison for Areal Unit Data, Spatial Statistics, vol. (Submitted) (November, 2017), pp. 89-106, Elsevier BV [doi]  [abs]
  39. Paci, L; Beamonte, MA; Gelfand, AE; Gargallo, P; Salvador, M, Analysis of residential property sales using space–time point patterns, Spatial Statistics, vol. 21 (August, 2017), pp. 149-165, Elsevier BV [doi]  [abs]
  40. Shirota, S; Gelfand, AE, Approximate Bayesian Computation and Model Assessment for Repulsive Spatial Point Processes, Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America, vol. 26 no. 3 (July, 2017), pp. 646-657, Informa UK Limited [doi]  [abs]
  41. Shirota, S; Gelfand, AE, Space and circular time log Gaussian Cox processes with application to crime event data, The Annals of Applied Statistics, vol. 11 no. 2 (June, 2017), pp. 481-503, Institute of Mathematical Statistics [doi]  [abs]
  42. Gelfand, AE; Banerjee, S, Bayesian Modeling and Analysis of Geostatistical Data., Annual Review of Statistics and Its Application, vol. 4 no. 1 (March, 2017), pp. 245-266 [doi]  [abs]
  43. Schliep, EM; Gelfand, AE; Clark, JS; Tomasek, BJ, Biomass prediction using a density-dependent diameter distribution model, The Annals of Applied Statistics, vol. 11 no. 1 (March, 2017), pp. 340-361, Institute of Mathematical Statistics [doi]  [abs]
  44. Paci, L; Gelfand, AE; Beamonte, MA; Rodrigues, M; Pérez-Cabello, F, Space-time modeling for post-fire vegetation recovery, Stochastic Environmental Research and Risk Assessment : Research Journal, vol. 31 no. 1 (January, 2017), pp. 171-183, Springer Nature [doi]  [abs]
  45. Leininger, TJ; Gelfand, AE, Bayesian inference and model assessment for spatial point patterns using posterior predictive samples, Bayesian Analysis, vol. 12 no. 1 (January, 2017), pp. 1-30, Institute of Mathematical Statistics [doi]  [abs]
  46. Taylor-Rodríguez, D; Kaufeld, K; Schliep, EM; Clark, JS; Gelfand, AE, Joint species distribution modeling: Dimension reduction using Dirichlet processes, Bayesian Analysis, vol. 12 no. 4 (January, 2017), pp. 939-967, Institute of Mathematical Statistics [doi]  [abs]
  47. Mastrantonio, G; Gelfand, AE; Jona Lasinio, G, The wrapped skew Gaussian process for analyzing spatio-temporal data, Stochastic Environmental Research and Risk Assessment : Research Journal, vol. 30 no. 8 (December, 2016), pp. 2231-2242, Springer Nature, ISSN 1436-3240 [doi]  [abs]
  48. Gelfand, AE; Schliep, EM, Spatial statistics and Gaussian processes: A beautiful marriage, Spatial Statistics, vol. 18 (November, 2016), pp. 86-104, Elsevier BV [doi]  [abs]
  49. Datta, A; Banerjee, S; Finley, AO; Gelfand, AE, On nearest-neighbor Gaussian process models for massive spatial data., Wiley Interdisciplinary Reviews. Computational Statistics, vol. 8 no. 5 (September, 2016), pp. 162-171 [doi]  [abs]
  50. Mastrantonio, G; Jona Lasinio, G; Gelfand, AE, Spatio-temporal circular models with non-separable covariance structure, Test, vol. 25 no. 2 (June, 2016), pp. 331-350, Springer Nature, ISSN 1133-0686 [doi]  [abs]
  51. Datta, A; Banerjee, S; Finley, AO; Gelfand, AE, Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets, Journal of the American Statistical Association, vol. 111 no. 514 (April, 2016), pp. 800-812, Informa UK Limited [doi]  [abs]
  52. Schliep, EM; Gelfand, AE; Clark, JS; Zhu, K, Modeling change in forest biomass across the eastern US, Environmental and Ecological Statistics, vol. 23 no. 1 (March, 2016), pp. 23-41, Springer Nature, ISSN 1352-8505 [doi]  [abs]
  53. Ghosh, S; Zhu, K; Gelfand, AE; Clark, JS, Joint Modeling of Climate Niches for Adult and Juvenile Trees, Journal of Agricultural, Biological, and Environmental Statistics, vol. 21 no. 1 (March, 2016), pp. 111-130, Springer Nature [doi]  [abs]
  54. Yu, R; Gelfand, A; Rajan, S; Shahabi, C; Liu, Y, Geographic segmentation via latent poisson factor model, Wsdm 2016 Proceedings of the 9th Acm International Conference on Web Search and Data Mining (February, 2016), pp. 357-366, ACM Press, ISBN 9781450337168 [doi]  [abs]
  55. Terres, MA; Gelfand, AE, Spatial process gradients and their use in sensitivity analysis for environmental processes, Journal of Statistical Planning and Inference, vol. 168 (January, 2016), pp. 106-119, Elsevier BV, ISSN 0378-3758 [doi]  [abs]
  56. Pan, J; Rao, V; Agarwal, PK; Gelfand, AE, Markov-modulated marked poisson processes for check-in data, 33rd International Conference on Machine Learning, Icml 2016, vol. 5 (January, 2016), pp. 3311-3320, ISBN 9781510829008  [abs]
  57. Rundel, CW; Schliep, EM; Gelfand, AE; Holland, DM, A data fusion approach for spatial analysis of speciated PM2.5 across time, Environmetrics, vol. 26 no. 8 (December, 2015), pp. 515-525, WILEY [doi]  [abs]
  58. Schliep, EM; Gelfand, AE; Clark, JS, Stochastic Modeling for Velocity of Climate Change, Journal of Agricultural, Biological, and Environmental Statistics, vol. 20 no. 3 (September, 2015), pp. 323-342, Springer Nature, ISSN 1085-7117 [doi]  [abs]
  59. Gelfand, AE; Banerjee, S, Bayesian wombling: Finding rapid change in spatial maps, Wiley Interdisciplinary Reviews. Computational Statistics, vol. 7 no. 5 (September, 2015), pp. 307-315, WILEY, ISSN 1939-5108 [doi]  [abs]
  60. Terres, MA; Gelfand, AE, Using spatial gradient analysis to clarify species distributions with application to South African protea, Journal of Geographical Systems, vol. 17 no. 3 (July, 2015), pp. 227-247, Springer Nature, ISSN 1435-5930 [doi]  [abs]
  61. Paci, L; Gelfand, AE; Cocchi, D, Quantifying uncertainty for temperature maps derived from computer models, Spatial Statistics, vol. 12 (May, 2015), pp. 96-108, Elsevier BV, ISSN 2211-6753 [doi]  [abs]
  62. Gelfand, AE, Comments on: Comparing and selecting spatial predictors using local criteria, Test, vol. 24 no. 1 (March, 2015), pp. 29-30 [doi]
  63. Finley, AO; Banerjee, S; Gelfand, AE, spBayes for large univariate and multivariate point-referenced spatio-temporal data models, Journal of Statistical Software, vol. 63 no. 13 (January, 2015), pp. 1-28, Foundation for Open Access Statistic, ISSN 1548-7660 [doi]  [abs]
  64. Wang, F; Gelfand, AE; Jona-Lasinio, G, Joint spatio-temporal analysis of a linear and a directional variable: Space-time modeling of wave heights and wave directions in the adriatic sea, Statistica Sinica, vol. 25 no. 1 (January, 2015), pp. 25-39, Institute of Statistical Science [doi]  [abs]
  65. Schliep, EM; Dong, TQ; Gelfand, AE; Li, F, Modeling individual tree growth by fusing diameter tape and increment core data, edited by Guttorp, P; Piegorsch, WW, Environmetrics, vol. 25 no. 8 (December, 2014), pp. 610-620, WILEY, ISSN 1180-4009 [doi]  [abs]
  66. Brynjarsdóttir, J; Gelfand, AE, On Covariate Importance for Regression Models with Multivariate Response, Journal of Agricultural, Biological, and Environmental Statistics, vol. 19 no. 4 (December, 2014), pp. 479-500, Springer New York LLC, ISSN 1085-7117 [doi]  [abs]
  67. Neelon, B; Gelfand, AE; Miranda, ML, A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores., Journal of the Royal Statistical Society. Series C, Applied Statistics, vol. 63 no. 5 (November, 2014), pp. 737-761, ISSN 0035-9254 [doi]  [abs]
  68. Wang, F; Gelfand, AE, Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes, Journal of the American Statistical Association, vol. 109 no. 508 (October, 2014), pp. 1565-1580, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  69. Gelfand, AE; Monteiro, JVD, Explaining return times for wildfires, Journal of Statistical Theory and Practice, vol. 8 no. 3 (July, 2014), pp. 534-545, Informa UK Limited, ISSN 1559-8608 [doi]  [abs]
  70. Clark, JS; Gelfand, AE; Woodall, CW; Zhu, K, More than the sum of the parts: forest climate response from joint species distribution models., Ecological Applications : a Publication of the Ecological Society of America, vol. 24 no. 5 (July, 2014), pp. 990-999, ISSN 1051-0761 [doi]  [abs]
  71. Paiva, T; Chakraborty, A; Reiter, J; Gelfand, A, Imputation of confidential data sets with spatial locations using disease mapping models., Statistics in Medicine, vol. 33 no. 11 (May, 2014), pp. 1928-1945, ISSN 0277-6715 [doi]  [abs]
  72. Allen, JM; Terres, MA; Katsuki, T; Iwamoto, K; Kobori, H; Higuchi, H; Primack, RB; Wilson, AM; Gelfand, A; Silander, JA, Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology., Global Change Biology, vol. 20 no. 4 (April, 2014), pp. 1251-1263, ISSN 1354-1013 [doi]  [abs]
  73. Nguyen, X; Gelfand, AE, Bayesian nonparametric modeling for functional analysis of variance, Annals of the Institute of Statistical Mathematics, vol. 66 no. 3 (January, 2014), pp. 495-526, ISSN 0020-3157 [doi]  [abs]
  74. Berrocal, VJ; Gelfand, AE; Holland, DM, Assessing exceedance of ozone standards: A space-time downscaler for fourth highest ozone concentrations, edited by Kuhnert, P, Environmetrics, vol. 25 no. 4 (January, 2014), pp. 279-291, WILEY, ISSN 1180-4009 [doi]  [abs]
  75. Ghosh, S; Bell, DM; Clark, JS; Gelfand, AE; Flikkema, PG, Process modeling for soil moisture using sensor network data, Statistical Methodology, vol. 17 no. C (January, 2014), pp. 99-112, Elsevier BV, ISSN 1572-3127 [doi]  [abs]
  76. Zhu, K; Woodall, CW; Ghosh, S; Gelfand, AE; Clark, JS, Dual impacts of climate change: forest migration and turnover through life history., Global Change Biology, vol. 20 no. 1 (January, 2014), pp. 251-264 [24014498], [doi]  [abs]
  77. Allen, JM; Terres, MA; Katsuki, T; Iwamoto, K; Kobori, H; Higuchi, H; Primack, RB; Wilson, AM; Gelfand, A; Silander, JA, Modeling daily flowering probabilities: Expected impact of climate change on Japanese cherry phenology, Global Change Biology, vol. 20 no. 4 (2014), pp. 1251-1263, ISSN 1354-1013 [doi]
  78. Gelfand, AE; Shin, J; Chertkov, M, Belief propagation for linear programming, Ieee International Symposium on Information Theory Proceedings (December, 2013), pp. 2249-2253, IEEE, ISBN 9781479904464 [doi]  [abs]
  79. Gelfand, AE; Ghosh, S; Clark, JS, Scaling integral projection models for analyzing size demography, Statistical Science, vol. 28 no. 4 (November, 2013), pp. 641-658, Institute of Mathematical Statistics, ISSN 0883-4237 [doi]  [abs]
  80. Allen, JM; Leininger, TJ; Hurd, JD; Civco, DL; Gelfand, AE; Silander, JA, Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation, Landscape Ecology, vol. 28 no. 9 (November, 2013), pp. 1671-1686, ISSN 0921-2973 [doi]  [abs]
  81. Berrocal, VJ; Miranda, ML; Gelfand, AE; Bhattacharya, S, Synthesizing categorical datasets to enhance inference, Statistical Methodology, vol. 15 (November, 2013), pp. 25-45, Elsevier BV, ISSN 1572-3127 [doi]  [abs]
  82. Leininger, TJ; Gelfand, AE; Allen, JM; Silander, JA, Spatial Regression Modeling for Compositional Data With Many Zeros, Journal of Agricultural, Biological, and Environmental Statistics, vol. 18 no. 3 (September, 2013), pp. 314-334, Springer Nature, ISSN 1085-7117 [doi]  [abs]
  83. Terres, MA; Gelfand, AE; Allen, JM; Silander, JA, Analyzing first flowering event data using survival models with space and time-varying covariates, Environmetrics, vol. 24 no. 5 (August, 2013), pp. 317-331, WILEY, ISSN 1180-4009 [doi]  [abs]
  84. Wang, F; Gelfand, AE, Directional data analysis under the general projected normal distribution., Statistical Methodology, vol. 10 no. 1 (July, 2013), pp. 113-127, ISSN 1572-3127 [doi]  [abs]
  85. Paci, L; Gelfand, AE; Holland, DM, Spatio-temporal modeling for real-time ozone forecasting., Spatial Statistics, vol. 4 (May, 2013), pp. 79-93, ISSN 2211-6753 [doi]  [abs]
  86. Chakraborty, A; Beamonte, MA; Gelfand, AE; Alonso, MP; Gargallo, P; Salvador, M, Spatial interaction models with individual-level data for explaining labor flows and developing local labor markets, Computational Statistics & Data Analysis, vol. 58 no. 1 (February, 2013), pp. 292-307, Elsevier BV, ISSN 0167-9473 [doi]  [abs]
  87. Chertkov, M; Gelfand, A; Shin, J, Loop calculus and bootstrap-belief propagation for perfect matchings on arbitrary graphs, Journal of Physics: Conference Series, vol. 473 no. 1 (January, 2013), pp. 012007-012007, IOP Publishing [doi]  [abs]
  88. Shin, J; Gelfand, AE; Chertkov, M, A graphical transformation for belief propagation: Maximum Weight Matchings and odd-sized cycles, Advances in Neural Information Processing Systems (January, 2013)  [abs]
  89. Nguyen, X; Gelfand, AE, Bayesian nonparametric modeling for functional analysis of variance, Annals of the Institute of Statistical Mathematics, vol. 66 no. 3 (2013), pp. 1-32, Springer Nature, ISSN 0020-3157 [doi]
  90. Allen, JM; Leininger, TJ; Hurd Jr, JD; Civco, DL; Gelfand, AE; Silander Jr, JA, Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation, Landscape Ecology, vol. 28 no. 9 (2013), pp. 1-16, Springer Nature, ISSN 0921-2973 [doi]  [abs]
  91. Heaton, MJ; Gelfand, AE, Kernel Averaged Predictors for Spatio-Temporal Regression Models., Spatial Statistics, vol. 2 no. 1 (December, 2012), pp. 15-32, ISSN 2211-6753 [doi]  [abs]
  92. Ghosh, S; Gelfand, AE; Clark, JS, Inference for Size Demography from Point Pattern Data using Integral Projection Models., Journal of Agricultural, Biological, and Environmental Statistics, vol. 17 no. 4 (December, 2012), pp. 641-677, ISSN 1085-7117 [doi]  [abs]
  93. Ghosh, S; Gelfand, AE; Clark, JS, Rejoinder, Journal of Agricultural, Biological, and Environmental Statistics, vol. 17 no. 4 (December, 2012), pp. 693-699, Springer Nature, ISSN 1085-7117 [doi]
  94. Gelfand, AE; Welling, M, Generalized belief propagation on tree robust structured region graphs, Uncertainty in Artificial Intelligence Proceedings of the 28th Conference, Uai 2012 (December, 2012), pp. 296-305, ISBN 9780974903989  [abs]
  95. Welling, M; Gelfand, AE; Ihler, A, A cluster-cumulant expansion at the fixed points of belief propagation, Uncertainty in Artificial Intelligence Proceedings of the 28th Conference, Uai 2012 (December, 2012), pp. 883-892, ISBN 9780974903989  [abs]
  96. Gelfand, AE; Sahu, SK; Holland, DM, On the Effect of Preferential Sampling in Spatial Prediction., Environmetrics, vol. 23 no. 7 (November, 2012), pp. 565-578, ISSN 1180-4009 [doi]  [abs]
  97. Lum, K; Gelfand, AE, Rejoinder, Bayesian Analysis, vol. 7 no. 2 (September, 2012), pp. 273-276, ISSN 1936-0975 [doi]
  98. Berrocal, VJ; Gelfand, AE; Holland, DM, Space-time data fusion under error in computer model output: an application to modeling air quality., Biometrics, vol. 68 no. 3 (September, 2012), pp. 837-848, ISSN 0006-341X [doi]  [abs]
  99. Ghosh, S; Gelfand, AE; Zhu, K; Clark, JS, The k-ZIG: flexible modeling for zero-inflated counts., Biometrics, vol. 68 no. 3 (September, 2012), pp. 878-885 [22348816], [doi]  [abs]
  100. Heaton, MJ; Gray, SC; Gelfand, AE, Process modelling for contingency tables with ordered categories, Statistical Modelling, vol. 12 no. 3 (June, 2012), pp. 211-228, SAGE Publications, ISSN 1471-082X [doi]  [abs]
  101. Lum, K; Gelfand, AE, Spatial Quantile Multiple Regression Using the Asymmetric Laplace Process, Bayesian Analysis, vol. 7 no. 2 (June, 2012), pp. 235-258, Institute of Mathematical Statistics [doi]
  102. Gelfand, AE, Hierarchical Modeling for Spatial Data Problems., Spatial Statistics, vol. 1 (May, 2012), pp. 30-39, ISSN 2211-6753 [doi]  [abs]
  103. Swamy, GK; Edwards, S; Gelfand, A; James, SA; Miranda, ML, Maternal age, birth order, and race: differential effects on birthweight., J Epidemiol Community Health, vol. 66 no. 2 (February, 2012), pp. 136-142 [21081308], [doi]  [abs]
  104. Jona-Lasinio, G; Gelfand, A; Jona-Lasinio, M, Spatial analysis of wave direction data using wrapped Gaussian processes, The Annals of Applied Statistics, vol. 6 no. 4 (January, 2012), pp. 1478-1498, Institute of Mathematical Statistics, ISSN 1932-6157 [doi]  [abs]
  105. Finley, AO; Banerjee, S; Gelfand, AE, Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes, Journal of Geographical Systems, vol. 14 no. 1 (January, 2012), pp. 29-47, Springer Nature, ISSN 1435-5930 [doi]  [abs]
  106. Ghosh, S; Gelfand, AE; Mølhave, T, Attaching uncertainty to deterministic spatial interpolations, Statistical Methodology, vol. 9 no. 1-2 (January, 2012), pp. 251-264, Elsevier BV, ISSN 1572-3127 [doi]  [abs]
  107. Anthopolos, R; James, SA; Gelfand, AE; Miranda, ML, A Spatial Measure of Neighborhood Level Racial Isolation Applied to Low Birthweight, Preterm Birth, and Birthweight in North Carolina, Spatial and Spatio Temporal Epidemiology, vol. 2 no. 4 (December, 2011), pp. 235-246 [22748223], [doi]  [abs]
  108. Guhaniyogi, R; Finley, AO; Banerjee, S; Gelfand, AE, Adaptive Gaussian Predictive Process Models for Large Spatial Datasets., Environmetrics, vol. 22 no. 8 (December, 2011), pp. 997-1007, ISSN 1180-4009 [doi]  [abs]
  109. Chen, Y; Gelfand, A; Fowlkes, CC; Welling, M, Integrating local classifiers through nonlinear dynamics on label graphs with an application to image segmentation, Proceedings of the Ieee International Conference on Computer Vision (December, 2011), pp. 2635-2642, IEEE, ISBN 9781457711015 [doi]  [abs]
  110. Kask, K; Gelfand, A; Otten, L; Dechter, R, Pushing the power of stochastic greedy ordering schemes for inference in graphical models, Proceedings of the National Conference on Artificial Intelligence, vol. 1 (November, 2011), pp. 54-60, ISBN 9781577355083  [abs]
  111. Gelfand, AE; Kask, K; Dechter, R, Stopping rules for randomized greedy triangulation schemes, Proceedings of the National Conference on Artificial Intelligence, vol. 2 (November, 2011), pp. 1043-1048, ISBN 9781577355090  [abs]
  112. Lum, K; Gelfand, AE, Local linear suppression for wireless sensor network data, Brazilian Journal of Probability and Statistics, vol. 25 no. 3 (November, 2011), pp. 392-405, Institute of Mathematical Statistics, ISSN 0103-0752 [doi]  [abs]
  113. Wilson, AM; Latimer, AM; Silander, JA; Gelfand, AE; de Klerk, H, Corrigendum to "A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation" [Ecol. Modell. 221 (January (1)) (2010) 106-112], Ecological Modelling, vol. 222 no. 18 (September, 2011), pp. 3456, Elsevier BV, ISSN 0304-3800 [doi]
  114. Nguyen, XL; Gelfand, AE, The dirichlet labeling process for clustering functional data, Statistica Sinica, vol. 21 no. 3 (July, 2011), pp. 1249-1289, Institute of Statistical Science, ISSN 1017-0405 [doi]  [abs]
  115. Gray, SC; Gelfand, AE; Miranda, ML, Hierarchical spatial modeling of uncertainty in air pollution and birth weight study., Statistics in Medicine, vol. 30 no. 17 (July, 2011), pp. 2187-2198 [21590788], [doi]  [abs]
  116. Clark, JS; Agarwal, P; Bell, DM; Flikkema, PG; Gelfand, A; Nguyen, X; Ward, E; Yang, J, Inferential ecosystem models, from network data to prediction., Ecological Applications : a Publication of the Ecological Society of America, vol. 21 no. 5 (July, 2011), pp. 1523-1536, ISSN 1051-0761 [21830699], [doi]  [abs]
  117. Heaton, MJ; Gelfand, AE, Spatial Regression Using Kernel Averaged Predictors, Journal of Agricultural, Biological, and Environmental Statistics, vol. 16 no. 2 (June, 2011), pp. 233-252, Springer Nature, ISSN 1085-7117 [doi]  [abs]
  118. Kim, D; Miranda, ML; Tootoo, J; Bradley, P; Gelfand, AE, Spatial modeling for groundwater arsenic levels in North Carolina., Environmental Science & Technology, vol. 45 no. 11 (June, 2011), pp. 4824-4831 [21528844], [doi]  [abs]
  119. Berrocal, VJ; Gelfand, AE; Holland, DM; Burke, J; Miranda, ML, On the use of a PM(2.5) exposure simulator to explain birthweight., Environmetrics, vol. 22 no. 4 (June, 2011), pp. 553-571, ISSN 1180-4009 [21691413], [doi]  [abs]
  120. Gray, SC; Gelfand, AE; Miranda, ML, SPATIAL ADJUSTMENT OF MEASUREMENT ERROR IN MATERNAL EXPOSURE TO AIR POLLUTION., American Journal of Epidemiology, vol. 173 (June, 2011), pp. S153-S153, OXFORD UNIV PRESS INC
  121. Gelfand, AE; Banerjee, S, Discussion on "Spatial prediction in the presence of positional error", Environmetrics, vol. 22 no. 2 (March, 2011), pp. 128, WILEY, ISSN 1180-4009 [doi]
  122. Wilson, AM; Silander, JA; Gelfand, A; Glenn, JH, Scaling up: Linking field data and remote sensing with a hierarchical model, International Journal of Geographical Information Science, vol. 25 no. 3 (March, 2011), pp. 509-521, Informa UK Limited, ISSN 1365-8816 [doi]  [abs]
  123. Chakraborty, A; Gelfand, AE; Wilson, AM; Latimer, AM; Silander, JA, Point pattern modelling for degraded presence-only data over large regions, Journal of the Royal Statistical Society. Series C, Applied Statistics, vol. 60 no. 5 (January, 2011), pp. 757-776, WILEY, ISSN 0035-9254 [doi]  [abs]
  124. Chakraborty, A; Gelfand, AE, Analyzing spatial point patterns subject to measurement error, Bayesian Analysis, vol. 5 no. 1 (December, 2010), pp. 97-122, Institute of Mathematical Statistics, ISSN 1936-0975 [doi]  [abs]
  125. Berrocal, VJ; Gelfand, AE; Holland, DM, A bivariate space-time downscaler under space and time misalignment., The Annals of Applied Statistics, vol. 4 no. 4 (December, 2010), pp. 1942-1975, ISSN 1932-6157 [doi]  [abs]
  126. Gelfand, AE; Chen, Y; Welling, M; Van Der Maaten, L, On herding and the perceptron cycling theorem, Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, Nips 2010 (December, 2010), ISBN 9781617823800  [abs]
  127. Chakraborty, A; Gelfand, AE; Wilson, AM; Latimer, AM; Silander, JA, Modeling large scale species abundance with latent spatial processes, The Annals of Applied Statistics, vol. 4 no. 3 (September, 2010), pp. 1403-1429, Institute of Mathematical Statistics, ISSN 1932-6157 [doi]  [abs]
  128. Schwartz, SL; Gelfand, AE; Miranda, ML, Joint Bayesian analysis of birthweight and censored gestational age using finite mixture models., Statistics in Medicine, vol. 29 no. 16 (July, 2010), pp. 1710-1723 [20575047], [doi]  [abs]
  129. Berrocal, VJ; Gelfand, AE; Holland, DM, A Spatio-Temporal Downscaler for Output From Numerical Models., Journal of Agricultural, Biological, and Environmental Statistics, vol. 15 no. 2 (June, 2010), pp. 176-197, ISSN 1085-7117 [doi]  [abs]
  130. Gray, SC; Gelfand, AE; Miranda, ML, HIERARCHICAL SPATIAL MODELING OF UNCERTAINTY IN AIR POLLUTION AND BIRTH WEIGHT STUDY, American Journal of Epidemiology, vol. 171 (June, 2010), pp. S79-S79, OXFORD UNIV PRESS INC
  131. Rodríguez, A; Dunson, DB; Gelfand, AE, Latent Stick-Breaking Processes., Journal of the American Statistical Association, vol. 105 no. 490 (April, 2010), pp. 647-659, ISSN 0162-1459 [23559690], [doi]  [abs]
  132. Sang, H; Gelfand, AE, Continuous spatial process models for spatial extreme values, Journal of Agricultural, Biological, and Environmental Statistics, vol. 15 no. 1 (January, 2010), pp. 49-65, Springer Nature, ISSN 1085-7117 [doi]  [abs]
  133. Wilson, AM; Latimer, AM; Silander, JA; Gelfand, AE; de Klerk, H, A Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation, Ecological Modelling, vol. 221 no. 1 (January, 2010), pp. 106-112, Elsevier BV, ISSN 0304-3800 [doi]  [abs]
  134. Tassone, EC; Miranda, ML; Gelfand, AE, Disaggregated spatial modelling for areal unit categorical data., Journal of the Royal Statistical Society. Series C, Applied Statistics, vol. 59 no. 1 (January, 2010), pp. 175-190, ISSN 0035-9254 [21151717], [doi]  [abs]
  135. Sahu, SK; Gelfand, AE; Holland, DM, Fusing point and areal level space-time data with application to wet deposition, Journal of the Royal Statistical Society. Series C, Applied Statistics, vol. 59 no. 1 (January, 2010), pp. 77-103, WILEY, ISSN 0035-9254 [doi]  [abs]
  136. Puggioni, G; Gelfand, AE, Analyzing space-time sensor network data under suppression and failure in transmission, Statistics and Computing, vol. 20 no. 4 (January, 2010), pp. 409-419, Springer Nature, ISSN 0960-3174 [doi]  [abs]
  137. Kask, K; Dechter, R; Gelfand, AE, Beem : BBucket Elimination with external memory, Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, Uai 2010 (January, 2010), pp. 268-276, ISBN 9780974903965  [abs]
  138. Miranda, ML; Swamy, GK; Edwards, S; Maxson, P; Gelfand, A; James, S, Disparities in maternal hypertension and pregnancy outcomes: evidence from North Carolina, 1994-2003., Public Health Reports (Washington, D.C. : 1974), vol. 125 no. 4 (2010), pp. 579-587, ISSN 0033-3549 [20597458], [doi]  [abs]
  139. Duan, JA; Gelfand, AE; Sirmansz, CF, Modeling space-time data using stochastic differential equations, Bayesian Analysis, vol. 4 no. 4 (December, 2009), pp. 733-758, Institute of Mathematical Statistics, ISSN 1936-0975 [doi]  [abs]
  140. Gelfand, AE; Smith, C; Colony, M; Bowman, C, Performance evaluation of decentralized estimation systems with uncertain communication, 2009 12th International Conference on Information Fusion, Fusion 2009 (November, 2009), pp. 786-793, ISBN 9780982443804  [abs]
  141. Petrone, S; Guindani, M; Gelfand, AE, Hybrid dirichlet mixture models for functional data, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 71 no. 4 (September, 2009), pp. 755-782, WILEY, ISSN 1369-7412 [doi]  [abs]
  142. Finley, AO; Sang, H; Banerjee, S; Gelfand, AE, Improving the performance of predictive process modeling for large datasets., Computational Statistics & Data Analysis, vol. 53 no. 8 (June, 2009), pp. 2873-2884, ISSN 0167-9473 [doi]  [abs]
  143. Anthopolos, R; James, S; Gelfand, AE; Berrocal, V; Miranda, ML, A NEIGHBORHOOD AND SPATIAL MEASURE OF RACIAL ISOLATION APPLIED TO BIRTHWEIGHT., American Journal of Epidemiology, vol. 169 (June, 2009), pp. S16-S16, OXFORD UNIV PRESS INC
  144. Sang, H; Gelfand, AE, Hierarchical modeling for extreme values observed over space and time, Environmental and Ecological Statistics, vol. 16 no. 3 (January, 2009), pp. 407-426, Springer Nature, ISSN 1352-8505 [doi]  [abs]
  145. Rodríguez, A; Dunson, DB; Gelfand, AE, Bayesian Nonparametric Functional Data Analysis Through Density Estimation., Biometrika, vol. 96 no. 1 (January, 2009), pp. 149-162, ISSN 0006-3444 [doi]  [abs]
  146. Sang, H; Gelfand, AE; Lennard, C; Hegerl, G; Hewitson, B, Interpreting self-organizing maps through space-time data models, The Annals of Applied Statistics, vol. 2 no. 4 (December, 2008), pp. 1194-1216, Institute of Mathematical Statistics, ISSN 1932-6157 [doi]  [abs]
  147. Liang, S; Carlin, BP; Gelfand, AE, ANALYSIS OF MINNESOTA COLON AND RECTUM CANCER POINT PATTERNS WITH SPATIAL AND NONSPATIAL COVARIATE INFORMATION., The Annals of Applied Statistics, vol. 3 no. 3 (October, 2008), pp. 943-962, Institute of Mathematical Statistics, ISSN 1932-6157 [doi]  [abs]
  148. Banerjee, S; Gelfand, AE; Finley, AO; Sang, H, Gaussian predictive process models for large spatial data sets., Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 70 no. 4 (September, 2008), pp. 825-848, ISSN 1369-7412 [doi]  [abs]
  149. Rodríguez, A; Dunson, DB; Gelfand, AE, The nested Dirichlet process: Rejoinder, Journal of the American Statistical Association, vol. 103 no. 483 (September, 2008), pp. 1153-1154, Informa UK Limited, ISSN 0162-1459 [doi]
  150. Gelfand, A; Smith, C; Colony, M; Bowman, C; Pei, R; Huynh, T; Brown, C, Advanced algorithms for distributed fusion, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 6974 (June, 2008), SPIE, ISBN 9780819471659 [doi]  [abs]
  151. Puggioni, G; Gelfand, AE; Elmore, JG, Joint modeling of sensitivity and specificity., Statistics in Medicine, vol. 27 no. 10 (May, 2008), pp. 1745-1761, ISSN 0277-6715 [doi]  [abs]
  152. Rappold, AG; Gelfand, AE; Holland, DM, Modeling mercury deposition through latent space-time processes., Journal of the Royal Statistical Society. Series C, Applied Statistics, vol. 57 no. 2 (April, 2008), pp. 187-205, ISSN 0035-9254 [doi]  [abs]
  153. Kottas, A; Duan, JA; Gelfand, AE, Modeling disease incidence data with spatial and spatio temporal dirichlet process mixtures., Biometrical Journal. Biometrische Zeitschrift, vol. 50 no. 1 (February, 2008), pp. 29-42, ISSN 0323-3847 [doi]  [abs]
  154. Rodríguez, A; Dunson, DB; Gelfand, AE, The nested dirichlet process, Journal of the American Statistical Association, vol. 103 no. 483 (January, 2008), pp. 1131-1154, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  155. Silberstein, A; Braynard, R; Filpus, G; Puggioni, G; Gelfand, A; Munagala, K; Yang, J, Data-driven processing in sensor networks, Cidr 2007 3rd Biennial Conference on Innovative Data Systems Research (December, 2007), pp. 10-21  [abs]
  156. Duan, JA; Guindani, M; Gelfand, AE, Generalized spatial dirichlet process models, Biometrika, vol. 94 no. 4 (December, 2007), pp. 809-825, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  157. Lee, KD; Gelfand, AE; Wiesenfeld, E; Stepnitz, B, Introduction of the hybrid inference tool (HIT), Fusion 2007 2007 10th International Conference on Information Fusion (December, 2007), IEEE, ISBN 0662478304 [doi]  [abs]
  158. Lee, KD; Wiesenfeld, E; Gelfand, A, Statistical comparison of a hybrid approach with approximate and exact inference models for fusion 2+, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 6567 (November, 2007), SPIE, ISBN 0819466891 [doi]  [abs]
  159. Gelfand, AE, Guest Editorial: Spatial and spatio-temporal modeling in environmental and ecological statistics, Environmental and Ecological Statistics, vol. 14 no. 3 (September, 2007), pp. 191-192, Springer Nature, ISSN 1352-8505 [doi]
  160. Barber, JJ; Gelfand, AE, Hierarchical spatial modeling for estimation of population size, Environmental and Ecological Statistics, vol. 14 no. 3 (September, 2007), pp. 193-205, Springer Nature, ISSN 1352-8505 [doi]  [abs]
  161. Gelfand, AE; Banerjee, S; Sirmans, CF; Tu, Y; Eng Ong, S, Multilevel modeling using spatial processes: Application to the Singapore housing market, Computational Statistics & Data Analysis, vol. 51 no. 7 (April, 2007), pp. 3567-3579, Elsevier BV, ISSN 0167-9473 [doi]  [abs]
  162. Woodard, DB; Gelfand, AE; Barlow, WE; Elmore, JG, Performance assessment for radiologists interpreting screening mammography., Statistics in Medicine, vol. 26 no. 7 (March, 2007), pp. 1532-1551, ISSN 0277-6715 [doi]  [abs]
  163. Majumdar, A; Gelfand, AE, Multivariate spatial modeling for geostatistical data using convolved covariance functions, Mathematical Geology, vol. 39 no. 2 (February, 2007), pp. 225-245, Springer Nature, ISSN 0882-8121 [doi]  [abs]
  164. Bhattacharya, S; Gelfand, AE; Holsinger, KE, Model fitting and inference under Latent Equilibrium Processes., Statistics and Computing, vol. 17 no. 2 (January, 2007), pp. 193-208, ISSN 0960-3174 [18836571], [doi]  [abs]
  165. Sahu, SK; Gelfand, AE; Holland, DM, High Resolution Space-Time Ozone Modeling for Assessing Trends., Journal of the American Statistical Association, vol. 102 no. 480 (January, 2007), pp. 1221-1234, ISSN 0162-1459 [doi]  [abs]
  166. Flikkema, PG; Agarwal, PK; Clark, JS; Ellis, C; Gelfand, A; Munagala, K; Yang, J, From data reverence to data relevance: Model-mediated wireless sensing of the physical environment, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4487 LNCS (January, 2007), pp. 988-994, ISSN 0302-9743, ISBN 9783540725831 [doi]  [abs]
  167. Silberstein, A; Puggioni, G; Gelfand, A; Munagala, K; Yang, J, Suppression and failures in sensor networks: A Bayesian approach, 33rd International Conference on Very Large Data Bases, Vldb 2007 Conference Proceedings (January, 2007), pp. 842-853, ISBN 9781595936493  [abs]
  168. Silberstein, A; Gelfand, AE; Munagala, K; Puggioni, G; Yang, J, Making Sense of Suppressions and Failures in Sensor Data: A Bayesian Approach., edited by Koch, C; Gehrke, J; Garofalakis, MN; Srivastava, D; Aberer, K; Deshpande, A; Florescu, D; Chan, CY; Ganti, V; Kanne, C-C; Klas, W; Neuhold, EJ, Vldb (2007), pp. 842-853, ACM, ISBN 978-1-59593-649-3
  169. Banerjee, S; Gelfand, AE, Bayesian Wombling: Curvilinear Gradient Assessment Under Spatial Process Models., Journal of the American Statistical Association, vol. 101 no. 476 (December, 2006), pp. 1487-1501, ISSN 0162-1459 [doi]  [abs]
  170. Gelfand, AE; Silander, JA; Wu, S; Latimer, A; Lewis, PO; Rebelo, AG; Holder, M, Rejoinder, Bayesian Analysis, vol. 1 no. 1 A (December, 2006), pp. 103-104, Institute of Mathematical Statistics, ISSN 1936-0975 [doi]
  171. Gelfand, AE; Silander, JA; Wu, S; Latimer, A; Lewis, PO; Rebelo, AG; Holder, M, Explaining species distribution patterns through hierarchical modeling, Bayesian Analysis, vol. 1 no. 1 A (December, 2006), pp. 41-92, Institute of Mathematical Statistics, ISSN 1936-0975 [doi]  [abs]
  172. Paliwal, P; Gelfand, AE, Estimating measures of diagnostic accuracy when some covariate information is missing., Statistics in Medicine, vol. 25 no. 17 (September, 2006), pp. 2981-2993, ISSN 0277-6715 [doi]  [abs]
  173. Clark, JS; Gelfand, AE, A future for models and data in environmental science., Trends in Ecology and Evolution, vol. 21 no. 7 (July, 2006), pp. 375-380, ISSN 0169-5347 [16815437], [doi]  [abs]
  174. Xia, G; Miranda, ML; Gelfand, AE, Approximately optimal spatial design approaches for environmental health data, Environmetrics, vol. 17 no. 4 (June, 2006), pp. 363-385, WILEY, ISSN 1180-4009 [doi]  [abs]
  175. Guindani, M; Gelfand, AE, Smoothness properties and gradient analysis under spatial Dirichlet process models, Methodology and Computing in Applied Probability, vol. 8 no. 2 (June, 2006), pp. 159-189, Springer Nature, ISSN 1387-5841 [doi]  [abs]
  176. Sahu, SK; Gelfand, AE; Holland, DM, Spatio-temporal modeling of fine particulate matter, Journal of Agricultural, Biological, and Environmental Statistics, vol. 11 no. 1 (March, 2006), pp. 61-86, Springer Nature, ISSN 1085-7117 [doi]  [abs]
  177. Majumdar, A; Munneke, HJ; Gelfand, AE; Banerjee, S; Slrmans, CF, Gradients in spatial response surfaces with application to urban land values, Journal of Business & Economic Statistics, vol. 24 no. 1 (January, 2006), pp. 77-90, Informa UK Limited, ISSN 0735-0015 [doi]  [abs]
  178. Paliwal, P; Gelfand, AE; Abraham, L; Barlow, W; Elmore, JG, Examining accuracy of screening mammography using an event order model., Statistics in Medicine, vol. 25 no. 2 (January, 2006), pp. 267-283, ISSN 0277-6715 [doi]  [abs]
  179. Barber, JJ; Gelfand, AE; Silander, JA, Modelling map positional error to infer true feature location, Canadian Journal of Statistics, vol. 34 no. 4 (January, 2006), pp. 659-676, WILEY, ISSN 0319-5724 [doi]  [abs]
  180. Flikkema, PG; Agarwal, PK; Clark, JS; Ellis, C; Gelfand, A; Munagala, K; Yang, J, Model-driven dynamic control of embedded wireless sensor networks, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3993 LNCS - III (January, 2006), pp. 409-416, Springer Berlin Heidelberg, ISSN 0302-9743 [doi]  [abs]
  181. Gelfand, AE; Latimer, A; Wu, S; Silander Jr, JA, Building Statistical Models to Analyze Species Distributions, Ecological Applications, vol. 16 no. 1 (2006), pp. 33-50, ISSN 1051-0761 [doi]  [abs]
  182. Short, M; Carlin, BP; Gelfand, AE, Bivariate spatial process modeling for constructing indicator or intensity weighted spatial CDFs, Journal of Agricultural, Biological, and Environmental Statistics, vol. 10 no. 3 (September, 2005), pp. 259-275, Springer Nature [doi]  [abs]
  183. Gelfand, AE; Kottas, A; Maceachern, SN, Bayesian nonparametric spatial modeling with dirichlet process mixing, Journal of the American Statistical Association, vol. 100 no. 471 (September, 2005), pp. 1021-1035, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  184. Gelfand, AE; Banerjee, S; Gamerman, D, Spatial process modelling for univariate and multivariate dynamic spatial data, Environmetrics, vol. 16 no. 5 (August, 2005), pp. 465-479, WILEY [doi]  [abs]
  185. Agarwal, DK; Silander, JA; Gelfand, AE; Dewar, RE; Mickelson, JG, Tropical deforestation in Madagascar: Analysis using hierarchical, spatially explicit, Bayesian regression models, Ecological Modelling, vol. 185 no. 1 (June, 2005), pp. 105-131, Elsevier BV [doi]  [abs]
  186. Gelfand, AE; Sahu, SK, On model expansion, model contraction, identifiability and prior information: Two illustrative scenarios involving mismeasured variables - Comment, Statistical Science, vol. 20 no. 2 (May, 2005), pp. 130-131, INST MATHEMATICAL STATISTICS [doi]  [abs]
  187. Majumdar, A; Gelfand, AE; Banerjee, S, Spatio-temporal change-point modeling, Journal of Statistical Planning and Inference, vol. 130 no. 1-2 (March, 2005), pp. 149-166, Elsevier BV [doi]  [abs]
  188. Gelfand, AE; Schmidt, AM; Wu, S; Silander, JA; Latimer, A; Rebelo, AG, Modelling species diversity through species level hierarchical modelling, Journal of the Royal Statistical Society. Series C, Applied Statistics, vol. 54 no. 1 (February, 2005), pp. 1-20, WILEY, ISSN 0035-9254 [doi]  [abs]
  189. Valente, J; Wu, SS; Gelfand, A; Sirmans, CF, Apartment rent prediction using spatial modeling, Journal of Real Estate Research, vol. 27 no. 1 (January, 2005), pp. 105-136  [abs]
  190. Agarwal, DK; Gelfand, AE, Slice sampling for simulation based fitting of spatial data models, Statistics and Computing, vol. 15 no. 1 (January, 2005), pp. 61-69, Springer Nature [doi]  [abs]
  191. 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
  192. 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
  193. Gelfand, AE; Valenti, J; Wu, S; Sirmans, CF, Apartment Rent Predictions Using Spatial Modeling, Journal of Real Estate Research, vol. 27 no. 27 (2005), pp. 1, 105-136
  194. 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]
  195. 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
  196. 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]
  197. Banerjee, S; Gelfand, AE; Knight, JR; Sirmans, CF, Spatial Modeling of House Prices Using Normalized Distance-Weighted Sums of Stationary Processes, Journal of Business & Economic Statistics, vol. 22 no. 2 (April, 2004), pp. 206-213, Informa UK Limited, ISSN 0735-0015 [doi]  [abs]
  198. Gelfand, AE, Discussion of “statistical research: Some advice for beginners” by M. Hamada and R. Sitter, The American Statistician, vol. 58 no. 3 (January, 2004), pp. 197-198, Informa UK Limited, ISSN 0003-1305 [doi]
  199. Gelfand, AE; Schmidt, AM; Banerjee, S; Sirmans, CF; Fuentes, M; Higdon, D; Sansó, B, Nonstationary multivariate process modeling through spatially varying coregionalization, Test, vol. 13 no. 2 (January, 2004), pp. 263-312, Springer Nature [doi]  [abs]
  200. Latimer, AM; Silander, JA; 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 (January, 2004), pp. 81-86  [abs]
  201. 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
  202. Gelfand, AE, Discussion to: Statistical Research: Some Advice for Beginners, The American Statistician no. 58 (2004), pp. 197-199
  203. 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
  204. Gelfand, AE; Ecker, MD; Knight, JR; Sirmans, CF, The Dynamics of Location in Home Price, Journal of Real Estate and Financial Economics, vol. 29 no. 29 (2004), pp. 149-166, Springer Nature, ISSN 0895-5638 [doi]  [abs]
  205. Schmidt, AM; Gelfand, AE, A Bayesian coregionalization approach for multivariate pollutant data, Journal of Geophysical Research, vol. 108 no. 24 (December, 2003), pp. STS 10-1 - STS 10-8 [doi]  [abs]
  206. Banerjee, S; Gelfand, AE; Sirmans, CF, Directional Rates of Change under Spatial Process Models, Journal of the American Statistical Association, vol. 98 no. 464 (December, 2003), pp. 946-954, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  207. 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 (August, 2003), pp. 537-557, WILEY [doi]  [abs]
  208. Ecker, MD; Gelfand, AE, Spatial modeling and prediction under stationary non-geometric range anistropy, Environmental and Ecological Statistics, vol. 10 no. 2 (June, 2003), pp. 165-178 [doi]  [abs]
  209. Fu, R; Gelfand, AE; Holsinger, KE, Exact moment calculations for genetic models with migration, mutation, and drift., Theoretical Population Biology, vol. 63 no. 3 (May, 2003), pp. 231-243 [doi]  [abs]
  210. Vlachos, PK; Gelfand, AE, On the calibration of Bayesian model choice criteria, Journal of Statistical Planning and Inference, vol. 111 no. 1-2 (February, 2003), pp. 223-234, Elsevier BV, ISSN 0378-3758 [doi]  [abs]
  211. 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 (January, 2003), pp. 239-250, WILEY [doi]  [abs]
  212. Gelfand, AE; Kottas, A, Bayesian Semiparametric Regression for Median Residual Life, Scandinavian Journal of Statistics, vol. 30 no. 4 (January, 2003), pp. 651-665, WILEY [doi]  [abs]
  213. Banerjee, S; Gelfand, AE, On smoothness properties of spatial processes, Journal of Multivariate Analysis, vol. 84 no. 1 (January, 2003), pp. 85-100, Elsevier BV [doi]  [abs]
  214. 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 (January, 2003), pp. 49-62, Informa UK Limited [doi]  [abs]
  215. 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]
  216. 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
  217. 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
  218. Gelfand, AE; Kim, HJ; Sirmans, CF; Banerjee, S, Spatial Modeling with spatially varying Coefficient Processes, Journal of the American Statistical Association, vol. 98 no. 98 (2003), pp. 387-396, Informa UK Limited [doi]  [abs]
  219. Gelfand, AE; Fu, R; Holsinger, K, Exact Moment Calculations for Genetic Models, Journal of Theoretical Population Biology no. 63 (2003), pp. 231-243
  220. Gelfand, AE; Schmidt, AM, A Bayesian Coregionalization Approach for Multivariate Pollutant Data, Journal of Geophysical Research, vol. Atmosphere no. 108 (2003), pp. D24, 8783, American Geophysical Union (AGU) [doi]  [abs]
  221. Gelfand, AE; Ecker, MD, Spatial Modeling and Prediction Under Range Anisotropy, Environmental and Ecological Statistics no. 10 (2003), pp. 165-178
  222. Agarwal, DK; Gelfand, AE; Citron-Pousty, S, Zero-inflated models with application to spatial count data, Environmental and Ecological Statistics, vol. 9 no. 4 (December, 2002), pp. 341-355 [doi]  [abs]
  223. Kottas, A; Branco, MD; Gelfand, AE, A nonparametric Bayesian modeling approach for cytogenetic dosimetry., Biometrics, vol. 58 no. 3 (September, 2002), pp. 593-600, ISSN 0006-341X [doi]  [abs]
  224. Agarwal, DK; Gelfand, AE; Silander, JA, Investigating tropical deforestation using two-stage spatially misaligned regression models, Journal of Agricultural, Biological, and Environmental Statistics, vol. 7 no. 3 (September, 2002), pp. 420-439, Springer Nature [doi]  [abs]
  225. Gelfand, AE; Kottas, A, A computational approach for full nonparametric Bayesian inference under Dirichlet process mixture models, Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America, vol. 11 no. 2 (August, 2002), pp. 289-305, Informa UK Limited, ISSN 1061-8600 [doi]  [abs]
  226. Brooks, SP; Smith, J; Vehtari, A; Plummer, M; Stone, M; Robert, CP; Titterington, DM; Nelder, JA; Atkinson, A; Dawid, AP; Lawson, A; Clark, A; Bernardo, JM; Sahu, SK; Richardson, S; Green, P; Burnham, KP; DeIorio, M; Draper, D; Gelfand, AE; Trevisani, M; Hodges, J; Lee, Y; De Luna, X; Meng, XL, Discussion on the paper by Spiegelhalter, Best, Carlin and van der Linde, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 64 no. 4 (January, 2002), pp. 616-639
  227. Clapp, JM; Kim, HJ; Gelfand, AE, Predicting spatial patterns of house prices using LPR and Bayesian smoothing, Real Estate Economics, vol. 30 no. 4 (January, 2002), pp. 505-532, WILEY [doi]  [abs]
  228. 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
  229. 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
  230. 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 [doi]  [abs]
  231. Gelfand, AE; Clapp, JM; Kim, HJ, Spatial Prediction of House Prices Using LPR and Bayesian Smoothing, Real Estate Economics, vol. 30 (2002)
  232. Gelfand, A; Agarwal, D; Pousty, S, Zero-inflated regression models for spatial count data, Environmental and Ecological Statistics (2002)
  233. Gelfand, A; Banerjee, S, Prediction, interpolation and regression for spatially misaligned data points, Sankhya A, vol. 64 (2002), pp. 227-245
  234. Gelfand, A; Trevisani, M, Discussion to "Bayesian measures of model complexity and fit, J. Royal Statistical Soc., vol. B (2002), pp. 631
  235. Gelfand, A; Wang, F, A simulation based approach to sample size determination under a given model and for separating models, Statistical Science, vol. 17 no. 2 (2002), pp. 193-208 [doi]  [abs]
  236. Gelfand, AE; Kottas, A, Nonparametric Bayesian modeling for stochastic order, Annals of the Institute of Statistical Mathematics, vol. 53 no. 4 (December, 2001), pp. 865-876 [doi]  [abs]
  237. Kottas, A; Gelfand, AE, Bayesian semiparametric median regression modeling, Journal of the American Statistical Association, vol. 96 no. 456 (December, 2001), pp. 1458-1468, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  238. Gelfand, AE; Carlin, BP; Trevisani, M, On computation using Gibbs sampling for multilevel models, Statistica Sinica, vol. 11 no. 4 (October, 2001), pp. 981-1003  [abs]
  239. Gelfand, A; Zhu, L; Carlin, BP, On the Change of Support Problem for Spatio-Temporal Data, Biostatistics, vol. 20 (2001), pp. 31-45
  240. Gelfand, A; Kottas, A, Modeling Variability Order: A Semiparametric Bayesian Approach, Methodology and Computing in Applied Probability, vol. 31 (2001), pp. 427-442
  241. 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
  242. Gelfand, AE; Ecker, MD; Christiansen, C; McLaughlin, TJ; Soumerai, SB, Conditional categorical response models with application to treatment of acute myocardial infarction, Journal of the Royal Statistical Society. Series C, Applied Statistics, vol. 49 no. 2 (December, 2000), pp. 171-186  [abs]
  243. Gelfand, AE, Gibbs Sampling, Journal of the American Statistical Association, vol. 95 no. 452 (December, 2000), pp. 1300-1304, Informa UK Limited, 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.) [doi]
  244. 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 (October, 2000), pp. 1657-1666, ISSN 0027-8874 [doi]  [abs]
  245. 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 (September, 2000), pp. 87-105, Elsevier BV [doi]  [abs]
  246. Mugglin, AS; Carlin, BP; Gelfand, AE, Fully model-based approaches for spatially misaligned data, Journal of the American Statistical Association, vol. 95 no. 451 (September, 2000), pp. 877-887, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  247. Gelfand, AE; Ghosh, SK; Christiansen, C; Soumerai, SB; McLaughlin, TJ, Proportional hazards models: A latent competing risk approach, Journal of the Royal Statistical Society. Series C: Applied Statistics, vol. 49 no. 3 (2000), pp. 385-397  [abs]
  248. Gelfand, A; Ghosh, SK; Christiansen, C; Soumerai, SB; McLaughlin, TJ, Proportional Hazards Models: A Latent Risks Approach, Applied Statistics, vol. 49 no. 3 (2000), pp. 385-397, WILEY [doi]  [abs]
  249. 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, WILEY [doi]  [abs]
  250. 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]
  251. 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
  252. Gelfand, A, Discussion to Bayesian Backfitting, Statistical Science, vol. 15 no. 3 (2000), pp. 217-218
  253. 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
  254. Gelfand, AE; Sahu, SK, Identifiability, Improper Priors, and Gibbs Sampling for Generalized Linear Models, Journal of the American Statistical Association, vol. 94 no. 445 (March, 1999), pp. 247-253, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  255. Ecker, MD; Gelfand, AE, Bayesian modeling and inference for geometrically anisotropic spatial data, Mathematical Geology, vol. 31 no. 1 (January, 1999), pp. 67-83 [doi]  [abs]
  256. 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]
  257. Carlin, BP; Kadane, JB; Gelfand, AE, Approaches for optimal sequential decision analysis in clinical trials., Biometrics, vol. 54 no. 3 (September, 1998), pp. 964-975, ISSN 0006-341X [doi]  [abs]
  258. Knight, JR; Sirmans, CF; Gelfand, AE; Ghosh, SK, Analyzing real estate data problems using the Gibbs sampler, Real Estate Economics, vol. 26 no. 3 (January, 1998), pp. 469-492, WILEY [doi]  [abs]
  259. Gelfand, AE; Ghosh, SK; Knight, JR; Sirmans, CF, Spatio-temporal modeling of residential sales data, Journal of Business & Economic Statistics, vol. 16 no. 3 (January, 1998), pp. 312-321, Informa UK Limited [doi]  [abs]
  260. Gelfand, AE; Ghosh, SK, Model choice: A minimum posterior predictive loss approach, Biometrika, vol. 85 no. 1 (January, 1998), pp. 1-11, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  261. Dey, DK; Gelfand, AE; Swartz, TB; Vlachos, PK, A simulation-intensive approach for checking hierarchical models, Test, vol. 7 no. 2 (January, 1998), pp. 325-346, Springer Nature [doi]  [abs]
  262. 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]
  263. Gelfand, AE; Ecker, MD, Modeling and Inference for Geometrically Anisotropic Spatial Data, Mathematical Geology, vol. 31 (1998), pp. 67-83
  264. Gelfand, AE; Ghosh, SK, Latent Waiting Time Models for Bivariate Event Times with Censoring, Sankhya B, vol. 60 (1998), pp. 31-47
  265. 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
  266. Dey, DK; Gelfand, AE; Peng, F, Overdispersed generalized linear models, Journal of Statistical Planning and Inference, vol. 64 no. 1 (October, 1997), pp. 93-107, Elsevier BV [doi]  [abs]
  267. 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 (September, 1997), pp. 836-845, Informa UK Limited [doi]  [abs]
  268. 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 (June, 1997), pp. 607-617, Informa UK Limited [doi]  [abs]
  269. Mukhopadhyay, S; Gelfand, AE, Dirichlet Process Mixed Generalized Linear Models, Journal of the American Statistical Association, vol. 92 no. 438 (June, 1997), pp. 633-639, Informa UK Limited [doi]  [abs]
  270. Ecker, MD; Gelfand, AE, Bayesian Variogram Modeling for an Isotropic Spatial Process, Journal of Agricultural, Biological, and Environmental Statistics, vol. 2 no. 4 (January, 1997), pp. 347-369, Springer Nature [doi]  [abs]
  271. Mallick, BK; Gelfand, AE, Semiparametric errors-in-variables models: A Bayesian approach, Journal of Statistical Planning and Inference, vol. 52 no. 3 (July, 1996), pp. 307-321, Elsevier BV [doi]  [abs]
  272. Gelfand, AE; Vlachos, P, Issues in Bayesian Clinical Trial Design for Categorical Endpoint Models, Proceedings of the Biometrics Section (1996), ASA Meeting
  273. Gelfand, AE; Sfiridis, J, Bayesian Analysis of Financial Event Study Data, Advances in Econometrics, vol. 11 (1996), pp. 25-62
  274. Gelfand, AE, Discussion to Empirical methods for combining likelihoods, J. Amer. Statist. Assoc., vol. 91 no. 434 (1996), pp. 551-552, Informa UK Limited [doi]
  275. Gelfand, AE; Sahu, SK; Carlin, BP, Efficient parametrisations for normal linear mixed models, Biometrika, vol. 82 no. 3 (September, 1995), pp. 479-488, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  276. Gelfand, AE; Mallick, BK, Bayesian analysis of proportional hazards models built from monotone functions., Biometrics, vol. 51 no. 3 (September, 1995), pp. 843-852, ISSN 0006-341X [doi]  [abs]
  277. Gelfand, AE; Mukhopadhyay, S, On Nonparametric Bayesian Inference for the Distribution of a Random Sample, Canadian Journal of Statistics, vol. 23 no. 4 (1995), pp. 411-420, WILEY [doi]  [abs]
  278. Gelfand, AE; Carlin, BP, Comment on Bayesian Computation and Stochastic Systems, Statistical Science, vol. 10 no. 1 (1995), pp. 43-46, Institute of Mathematical Statistics [doi]
  279. 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]
  280. 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, Informa UK Limited [doi]  [abs]
  281. Gelfand, AE; Sahu, S, On Markov chain Monte Carlo acceleration, Journal of Computational and Graphical Statistics, vol. 3 no. 3 (1995), pp. 261-276, Informa UK Limited [doi]  [abs]
  282. Gelfand, AE; Mallick, B, Discussion to Assessment and Propagation of Model Uncertainty, J. Royal Stat. Soc. B, vol. 57 (1995), pp. 82-83
  283. Mallick, BK; Gelfand, AE, Generalized linear models with unknown link functions, Biometrika, vol. 81 no. 2 (June, 1994), pp. 237-245, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  284. Gelfand, AE; Pai, J; Ravishanker, N, Bayesian analysis of concurrent time series with application to regional IBM revenue data, Journal of Forecasting, vol. 13 no. 5 (1994), pp. 463-479, WILEY [doi]  [abs]
  285. Gelfand, AE; Dey, D, Bayesian model choice: asymptotic and exact calculations, Journal Royal Statistical Society B, vol. 56 (1994), pp. 501-514
  286. Carlin, BP; Gelfand, AE, Parametric likelihood inference for record breaking problems, Biometrika, vol. 80 no. 3 (September, 1993), pp. 507-515, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  287. 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, WILEY [doi]  [abs]
  288. Gelfand, AE, Discussion to Approximate Bayesian Inference with the Weighted Likelihood Bootstrap, J. Royal Statistical Society B, vol. 56 (1993), pp. 36-37
  289. 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
  290. 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
  291. 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
  292. Crabtree, BF; Gelfand, AE; Miller, WL; Zyzanski, S; O'Connor, PJ; Winsemius, D, Categorical data analysis in primary care research: log-linear models., Family Medicine, vol. 24 no. 2 (February, 1992), pp. 145-151  [abs]
  293. Lange, N; Carlin, BP; Gelfand, AE, Rejoinder, Journal of the American Statistical Association, vol. 87 no. 419 (January, 1992), pp. 631-632, Informa UK Limited [doi]
  294. Gelfand, AE, Comment, Statistical Science, vol. 7 no. 4 (January, 1992), pp. 486-487, Institute of Mathematical Statistics [doi]
  295. Gelfand, AE, Discussion to Constrained Monte Carlo maximum likelihood for dependent data, Journal Royal Statistical Society B, vol. 54 (1992), pp. 690-691
  296. 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 no. 419 (1992), pp. 615-632, Informa UK Limited (JASA applications paper of the year.) [doi]  [abs]
  297. Gelfand, AE; Smith, AFM; Lee, TM, Bayesian analysis of constrained parameter and truncated data problems, Journal Amer. Stat. Assoc., vol. 87 no. 418 (1992), pp. 523-532, Informa UK Limited [doi]  [abs]
  298. Gelfand, AE; Smith, AFM, Bayesian statistics without tears: a sampling-resampling perspective, American Statistician, vol. 46 no. 2 (1992), pp. 84-88, Informa UK Limited [doi]  [abs]
  299. Gelfand, ; E, A; 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, WILEY [doi]  [abs]
  300. 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]
  301. Gelfand, AE; Carlin, B; Smith, AFM, Hierarchical Bayesian analysis of change point problems, Applied Statistics, vol. 41 (1992), pp. 389-405
  302. Wakefield, JC; Gelfand, AE; Smith, AFM, Efficient generation of random variates via the ratio-of-uniforms method, Statistics and Computing, vol. 1 no. 2 (December, 1991), pp. 129-133, Springer Nature, ISSN 0960-3174 [doi]  [abs]
  303. Carlin, BP; Gelfand, AE, An iterative Monte Carlo method for nonconjugate Bayesian analysis, Statistics and Computing, vol. 1 no. 2 (December, 1991), pp. 119-128, Springer Nature, ISSN 0960-3174 [doi]  [abs]
  304. Gelfand, AE; Kuo, L, Nonparametric Bayesian bioassay including ordered polytomous response, Biometrika, vol. 78 no. 3 (September, 1991), pp. 657-666, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  305. 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, Informa UK Limited [doi]  [abs]
  306. Gelfand, AE; Hills, SE; Racine-Poon, A; Smith, AFM, Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling, Journal of the American Statistical Association, vol. 85 no. 412 (December, 1990), pp. 972-972, JSTOR [doi]  [abs]
  307. Gelfand, AE; Dalal, SR, A note on overdispersed exponential families, Biometrika, vol. 77 no. 1 (December, 1990), pp. 55-64, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  308. Gelfand, AE; Hills, SE; Racine-Poon, A; Smith, AFM, Illustration of Bayesian inference in normal data models using Gibbs sampling, Journal of the American Statistical Association, vol. 85 no. 412 (January, 1990), pp. 972-985 [doi]  [abs]
  309. Gelfand, AE; Smith, AFM, Sampling-based approaches to calculating marginal densities, Journal of the American Statistical Association, vol. 85 no. 410 (January, 1990), pp. 398-409, JSTOR (Reprinted in "Breakthroughs in Statistics".) [doi]  [abs]
  310. Gelfand, AE; Dey, DK, On measuring Bayesian robustness of contaminated classes of priors, Statistics and Decisions, vol. 9 (1990), pp. 63-80
  311. 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
  312. Gelfand, AE; Carlin, B, Approaches for Empirical Bayes Confidence Intervals, Journal Amer. Stat. Assoc., vol. 85 no. 409 (1990), pp. 105-114, Informa UK Limited [doi]  [abs]
  313. Dey, DK; Gelfand, AE, Improved estimation of a patterned covariance matrix, Journal of Multivariate Analysis, vol. 31 no. 1 (January, 1989), pp. 107-116, Elsevier BV, ISSN 0047-259X [doi]  [abs]
  314. Gelfand, AE; Carlin, B, Apoproaches for Empirical Bayes Confidence Intervals for a Vector of Exponential Scale Parameters, Computing Science and Statistics Interface (1989), pp. 485-498, 1988 ASA
  315. Gelfand, AE; Leeds, S, Estimation for Dirichlet Mixed Models, Naval Research Logistics Quart., vol. 36 no. 2 (1989), pp. 197-214, WILEY [doi]  [abs]
  316. Gelfand, AE; Dey, DK, Improved estimation of the disturbance variance in a linear regression model, Journal of Econometrics, vol. 39 no. 3 (January, 1988), pp. 387-395, Elsevier BV, ISSN 0304-4076 [doi]  [abs]
  317. Gelfand, AE; Dey, DK, On the estimation of a variance ratio, Journal of Statistical Planning and Inference, vol. 19 no. 1 (January, 1988), pp. 121-131, Elsevier BV, ISSN 0378-3758 [doi]  [abs]
  318. Gelfand, A.E., Estimation of a Restricted Variance Ratio, Proceedings of 2nd International Tampere Conference in Statistics (1988), pp. 457-466
  319. Gelfand, AE; Dey, DK, Improved Estimation of Variance Components in Mixed Models, Commun. in Statistics A, vol. 17 no. 10 (1988), pp. 3313-3331, Informa UK Limited [doi]  [abs]
  320. Gelfand, AE; Das Gupta, A; Dey, DK, A new admissibility theorem with applications to estimation of survival and hazard rates and means in the scale parameter family, Sankhya A, vol. 50 no. 2 (1988), pp. 269-281
  321. Gelfand, AE; Dey, DK, Improved Estimation of a Disturbance Variance, Journal of Econometrics, vol. 39 no. 3 (1988), pp. 387-395, ISSN 0304-4076  [abs]
  322. Contributions to the Theory and Application of Statistics, edited by Gelfand, A.E. (1987)
  323. Gelfand, AE, Estimation in Parametric Mixture Families, Contributions to the Theory and Application of Statistics (1987), pp. 379-396
  324. Gelfand, AE, Mean Square Error Behavior for Prediction in Linear Regression, Communications in Statistics, vol. 16 no. 6 (1987), pp. 1717-1724, Informa UK Limited [doi]  [abs]
  325. Gelfand, AE, Reconsidering Inference in Conjoint Analysis, Proceedings of Asa Business and Economics Section (1987), pp. 135-141
  326. CATTIN, P; GELFAND, A, A NEW NONMETRIC CONJOINT METHOD - SOME PRELIMINARY-RESULTS, Advances in Consumer Research, vol. 13 (1986), pp. 460-462, ISSN 0098-9258 [Gateway.cgi]
  327. Proceedings of the Second Workshop on Law and Justice Statistics, edited by Gelfand, A.E. (1984), Bureau of Justice Statistics, Washington, D.C.
  328. Gelfand, A.E. and W.R. Stephenson, An examination of U.S. appellate court opinions, Proceedings of the Second Workshop on Law and Justice Statistics (1984), pp. 37-45, Washington, D.C.
  329. Gelfand, AE, On attribute importance and relative market shares in conjoint analysis, Proceedings of the Business and Economics Statistics Section (1984), pp. 243-248, ASA Meeting
  330. Gelfand, AE, Estimation in concentral distributions, Commun. in Statist., vol. 12 no. 4 (1983), pp. 463-475, Informa UK Limited [doi]  [abs]
  331. Gelfand, AE; Cattin, P; Danes, J, A simple Bayesian procedure for estimation in a conjoint model, J. of Marketing Research, vol. XX (1983), pp. 29-35
  332. Gelfand, AE, A behavioral summary for completely random nets, Bulletin of Mathematical Biology, vol. 44 no. 3 (May, 1982), pp. 309-320, Springer Nature, ISSN 0092-8240 [doi]  [abs]
  333. Gelfand, AE; Walker, CC, On the character of an distance between states in a binary switching net., Biological Cybernetics, vol. 43 no. 2 (January, 1982), pp. 79-86, ISSN 0340-1200 [doi]  [abs]
  334. Gelfand, AE, An Estimation Problem with Poisson Processes, Australian Journal of Statistics, vol. 23 no. 2 (January, 1981), pp. 224-231, WILEY [doi]  [abs]
  335. Gelfand, AE, An estimation problem for Poisson processes, Australian Journal of Statistics, vol. 23 no. 2 (1981), pp. 1-8
  336. Gelfand, AE; Shuchman, P, Can judges select cases of "No Precedential Value"?, Emory Law Review, vol. 29 (1980), pp. 193-228
  337. Gelfand, AE; Walker, CC, A system theoretic approach to the management of complex organizations: Management by consensus and its interaction with other management strategies, Behavioral Science, vol. 25 no. 4 (1980), pp. 250-260, WILEY [doi]  [abs]
  338. Walker, CC; Gelfand, AE, A system theoretic approach to the management of complex organizations: Management by exception, priority, and input span in a class of fixed‐structure models, Behavioral Science, vol. 24 no. 2 (January, 1979), pp. 112-120, WILEY [doi]  [abs]
  339. Gelfand, AE; Stephenson, WR, A model for precedential value of appellate court decisions, Proceedings of the Social Statistics Section (1979), pp. 559-563, ASA Meeting
  340. Gelfand, AE; Davis, JE, The jury list in Connecticut: Is the voter registration list truly representative?, Connecticut Bar Journal, vol. 52 no. 6 (1978), pp. 449-474
  341. Gelfand, AE; Walker, CC, A model for complex organization with applications to managerial strategy and advertising policy, Proceedings of the Business and Economic Statistics Section (1978), pp. 232-236, 1978 ASA Meeting
  342. Gelfand, AE; Walker, CC, The Distribution of Cycle Lengths in a Class of Abstract Systems, International Journal of General Systems, vol. 4 no. 1 (January, 1977), pp. 39-45, Informa UK Limited [doi]  [abs]
  343. Gelfand, AE; Solomon, H, Rejoinder to On the Effect of Jury Size, J. Amer. Statist. Assoc., vol. 72 no. 359 (1977), pp. 536-537, Informa UK Limited [doi]
  344. Gelfand, AE, Toward characterizing Boolean transformations, Proceedings of the Society for General Systems Research (1977), pp. 111-116
  345. Gelfand, AE, Are 6-member juries really as good as 12-member juries?, Trial Magazine, vol. 13 no. 2 (1977), pp. 41-43
  346. Gelfand, AE; Solomon, H, Considerations in building jury behavior models, Jurimetrics Journal, vol. 17 no. 4 (1977), pp. 292-314
  347. Gelfand, AE; Walker, CC, The distribution of cycle lengths in a class of abstract systems, Internat. J. General Syst., vol. 2 no. 4 (1977), pp. 39-46
  348. Gelfand, AE, COMPARISON OF SEVERAL ATTRIBUTE SAMPLING PLANS., Naval Research Logistics, vol. 23 no. 3 (January, 1976), pp. 513-523  [abs]
  349. Gelfand, AE; Thomas, DL, Discrimination between the binomial and hypergeometric models, Commun. in Statist., vol. 5 no. 3 (1976), pp. 225-240, Informa UK Limited [doi]  [abs]
  350. Gelfand, AE; Solomon, H, analyzing the decision making process of the American jury, J. Amer. Statist. Assoc., vol. 70 no. 350 (1975), pp. 305-310, Informa UK Limited [doi]  [abs]
  351. Gelfand, AE; Solomon, H, Modeling jury verdicts for the American legal system, J. Amer. Statist. Assoc., vol. 69 no. 345 (1974), pp. 32-38, Informa UK Limited [doi]  [abs]
  352. Gelfand, AE; Thomas, DL, Confidence coefficients for binomial interval estimates under hypergeometric models, Amer. Statistician, vol. 28 no. 2 (1974), pp. 52-56, Informa UK Limited [doi]
  353. Gelfand, AE, Rapid seriation methods for multivariate observations through similarities, Commun. in Statist., vol. 3 no. 7 (1974), pp. 635-645
  354. Gelfand, AE; Solomon, H, A study of Poisson's models for jury verdicts in criminal and civil trials, J. Amer. Statist. Assoc., vol. 68 no. 342 (1973), pp. 271-278, Informa UK Limited [doi]  [abs]
  355. Gelfand, AE, Rapid seriation methods with archaeological applications, Mathematics in the Archaeological and Historical Sciences (1971), pp. 186-201, Edinburgh University Press
  356. Gelfand, AE, Seriation Methods for arthaeological materials, American Antiquity, vol. 36 no. 3 (1971), pp. 263-274, Cambridge University Press (CUP) [doi]  [abs]

Book Reviews

  1. Gelfand, A.E., Review of "Statistical Methods in Discrimination Litigation" by D.H. Kaye and M. Aicken, Jurimetrics, vol. 27 no. 3 (1987), pp. 325-327
  2. Gelfand, A.E., Review of "An Economic Analysis of Crime" by P. Schmidt and A. Witte, JASA, vol. 81 (1986), pp. 250-251
  3. Gelfand, A.E., Review of "Prediction in Criminology" by D.P. Farrington and R. Tarling, JASA, vol. 81 (1986), pp. 872-873

Chapters

  1. Gelfand, AE, Multivariate Spatial Process Models, in Handbook of Regional Science: Second and Extended Edition: With 238 Figures and 78 Tables (January, 2021), pp. 1985-2016, ISBN 9783662607220 [doi]  [abs]
  2. Trevisani, M; Gelfand, A, Spatial misalignment models for small area estimation: A simulation study, in Studies in Theoretical and Applied Statistics, Selected Papers of the Statistical Societies, vol. Part F3 (January, 2013), pp. 269-279, Springer Berlin Heidelberg, ISBN 9783642355875 [doi]  [abs]
  3. Gelfand, AE; Banerjee, S; Finley, AO, Spatial Design for Knot Selection in Knot-Based Dimension Reduction Models, in Spatio-temporal Design: Advances in Efficient Data Acquisition (October, 2012), pp. 142-169, JOHN WILEY & SONS LTD, ISBN 9780470974292 [doi]  [abs]
  4. 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
  5. A. Gelfand, Bayesian Computation, in Encyclopedia of Environmetrics, edited by A.H. El-Shaarawi and W.W. Piegorsch, vol. 1 (2002), pp. 150-151
  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. Gelfand, AE, Gibbs sampling, in Statistics in the 21st Century, edited by A.E. Raftery, M.A. Tanner, M.T. Wells (January, 2001), pp. 341-349, Chapman Hall/CRC, Boca Raton, ISBN 1584882727  [abs]
  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. Gelfand, A.E. with P.K. Vlachos, Nonparametric Bayesian Group Sequential Design, in Practical Nonparametric and Semiparametric Bayesian Statistics, edited by D. Dey, P. Mueller and D. Sinha (1998), pp. 115-132, Springer Verlag Lecture Notes
  13. Gelfand, A.E., Approaches to Semiparametric Bayesian Regression, in Asymptotics, Nonparametrics and Time Series, edited by Subir Ghosh (1998), pp. 615-638, Marcel Dekker, Inc., New York
  14. Gelfand, A.E., Gibbs Sampling, in Encyclopedia of Statistical Sciences (update), edited by J. Kotz, C. Read, D. Banks (1997), pp. 283-291, J. Wiley and Sons, New York
  15. Gelfand, A.E. with S. Sahu and B. Carlin, Efficient Parametrization for Generalized Linear Mixed Models, in Bayesian Statistics 5, edited by J. Bernardo, et al. (1996), pp. 165-180, Clarendon Press, Oxford
  16. Gelfand, A.E., Model Determination Using Sampling-Based Methods, in Markov Chain Monte Carlo In Practice, edited by W. Gilks, S. Richardson and D. Spiegelhalter (1995), pp. 145-161, Chapman Hall, London
  17. Gelfand, A.E. with J. Marriott, N. Ravishanker, J. Pai, Bayesian analysis of ARMA processes: complete sampling based inference under exact likelihoods, in Bayesian Statistics and Econometrics: Essays in Honor of Arnold Zellner, edited by D. Berry, K. Chaloner and J. Geweke (1995), pp. 241-256, J. Wiley and Sons, New York
  18. Gelfand, A.E. and C. Yiannoutsos, Subgraph approximations for large directed graphical models, in Statistical Decision Theory & Related Topics V, edited by J. Berger and S. Gupta (1993), pp. 441-452, Springer-Verlag, New York
  19. Gelfand, A.E. and B. Carlin, Bayesian inference for hard problems using the Gibbs sampler, in Computing Science and Statistics Interface 1990, edited by C. Page, R. LePage (1992), pp. 29-37, Springer-Verlag, New York
  20. Gelfand, A.E. and D. Dey, H. Chang, Model determination using predictive distributions with implementation via sampling based methods (with discussion), in Bayesian Statistics 4, edited by J. Bernardo et al. (1992), pp. 147-167, Oxford University PRess
  21. Gelfand, A.E., Statistics in Archaeology, in Encyclopedia of Statistical Sciences, vol. I (1980), pp. 118-22, John Wiley & Sons, Inc.
  22. Gelfand, A.E. and C.C. Walker, Managing Complex Systems: An Application of Ensemble Methods in System Theory, in Applied General Systems Reseach, Recent Developments and Trends, edited by G. Klir (1978), pp. 175-85, New York: Plenum Press
  23. Gelfand, A.E. and H. Solomon, An argument in favor of 12-member juries, in Modeling the Criminal Justice System (March 1977), pp. 205-23, Sage Criminal Justice System Annals, Sage Publications