BOOK

  • Kedem, B., De Oliveira, V. and Sverchkov, M. (2017), Statistical Data Fusion, World Scientific.

    • ARTICLES

  • Nguyen, Q.N. and De Oliveira, V. (2025), "Approximating Gaussian Copula Models for Count Time Series: Connecting the Distributional Transform and a Continuous Extension," Journal of Applied Statistics, to appear.

  • Gu, M. and De Oliveira, V. (2025), "Prior Distributions for Gaussian Processes in Computer Model Emulation and Calibration." In: Handbook of Statistical Methods for Computer Modeling, D. Bingham, M. Haran, J. Oakley and B. Sanso (eds.) Chapman & Hall/CRC, to appear.

  • Han, Z. and De Oliveira, V. (2025), "Default Priors for the Smoothness Parameter in Gaussian Matern Random Fields," Bayesian Analysis, to appear.

  • Reyna, V., Fathesami, N., Wu, W., Muluk, S.C., De Oliveira, V. and Finol, E.A. (2025), "On The Relative Effects of Wall and Intraluminal Thrombus Constitutive Material Properties in Abdominal Aortic Aneurysm Wall Stress," Cardiovascular Engineering and Technology, 16, 66-78.

  • De Oliveira, V. (2023), "A Simple Isotropic Correlation Family in R^3 with Long-Range Dependence and Flexible Smoothness." In: Research Papers in Statistical Inference for Time Series and Related Models---Essays in Honor of Masanobu Taniguchi, Y. Liu, J. Hirukawa and Y. Kakizawa (eds.), Springer, pp 111-122.

  • De Oliveira, V. and Han, Z. (2023), "Approximate Reference Priors for Gaussian Random Fields," Scandinavian Journal of Statistics, 50, 296-326.

  • De Oliveira, V. and Han, Z. (2022), "On Information About Covariance Parameters in Gaussian Mat\'ern Random Fields," Journal of Agricultural, Biological and Environmental Statistics, 27, 690-712.

  • De Oliveira, V. and Ecker, M. (2022), "A Non--Stationary Non--Gaussian Hedonic Spatial Model for House Selling Prices," Communications in Statistics--Simulation and Computation, 51, 2888-2905.

  • Han, Z. and De Oliveira, V. (2020), "Maximum Likelihood Estimation of Gaussian Copula Models for Geostatistical Count Data," Communications in Statistics--Simulation and Computation, 49, 1957-1981.

  • Canchi, T., Patnaik, S.S., Nguyen, H.N., Ng, E.Y.K., Narayanan, S., Muluk, S.C., De Oliveira, V. and Finol, E.A. (2020), "A Comparative Study of Biomechanical and Geometrical Attributes of Abdominal Aortic Aneurysms in the Asian and Caucasian Populations," Journal of Biomechanical Engineering, 142(6), 061003.

  • De Oliveira, V. (2020), "Models for Geostatistical Binary Data: Properties and Connections," The American Statistician, 74, 72-79.

  • Wu, W., Rengarajan, B., Thirugnanasambandam, M., Parikh, S.A., Gomez, R., De Oliveira, V., Muluk, S.C. and Finol, E.A. (2019), "Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms," Annals of Biomedical Engineering, 47, 1611-1625.

  • Han, Z. and De Oliveira, V. (2018), "gcKrig: An R Package for the Analysis of Geostatistical Count Data Using Gaussian Copulas," Journal of Statistical Software, 87 (13), 1-32.

  • Parikh, S.A., Gomez, R., Thirugnanasambandam, M., Chauhan, S.S., De Oliveira, V., Muluk, S.C., Eskandari, M.K. and Finol, E.A. (2018), "Decision Tree Based Classification of Abdominal Aortic Aneurysms Using Geometry Quantification Measures," Annals of Biomedical Engineering, 2135-2147.

  • De Oliveira, V., Wang, B. and Slud, E.V. (2018), "Spatial Modeling of Rainfall Accumulated Over Short Periods of Time," Journal of Multivariate Analysis, 166, 129-149.

  • Kedem, B. and De Oliveira, V. (2018), "On Joint Analysis of Testicular Germ Cell Cancer." Journal of Urology and Research, 5(1), 1097.

  • De Oliveira, V. and Kedem, B. (2017), "Bayesian Analysis of a Density Ratio Model," The Canadian Journal of Statistics, 45, 274-289.

  • Chauhan, S.S., Gutierrez, C.A., Thirugnanasambandam, M., De Oliveira, V., Muluk, S.C., Eskandari, M.K. and Finol, E.A. (2017), "The Association Between Geometry and Wall Stress in Emergently Repaired Abdominal Aortic Aneurysms," Annals of Biomedical Engineering, 45, 1908-1916.

  • Han, Z. and De Oliveira, V. (2016), "On the Correlation Structure of Gaussian Copula Models for Geostatistical Count Data," Australian and New Zealand Journal of Statistics, 58, 47-69.

  • De Oliveira, V. and Kone, B. (2015), "Prediction Intervals for Integrals of Some Types of Non-Gaussian Random Fields: A Semiparametric Bootstrap Approach." In: JSM Proceedings, Statistics and the Environment Section. Alexandria, VA: American Statistical Association, pp 2588-2597.

  • De Oliveira, V. and Kone, B. (2015), "Prediction Intervals for Integrals of Gaussian Random Fields," Computational Statistics and Data Analysis, 83, 37-51.

  • Jing, L. and De Oliveira, V. (2015), "geoCount: An R Package for the Analysis of Geostatistical Count Data," Journal of Statistical Software, 63 (11), 1-33.

  • De Oliveira, V. and Trindade, A.A. (2014), "Spatial Statistics." In: Encyclopedia of Social Network Analysis and Mining, R. Alhajj and J. Rokne (eds.) Springer, pp 1976-1990.

  • Raut, S.S., Jana, A., De Oliveira, V., Muluk, S.C. and Finol, E.A. (2014), "The Effect of Uncertainty in Wall Vascular Material Properties on Abdominal Aortic Aneurysm Wall Mechanics." In: Computational Biomechanics for Medicine, B. Doyle, K. Miller, A. Wittek, and P.M.F. Nielsen (eds.) Springer, pp 69-89.

  • De Oliveira, V. (2014), "Poisson Kriging: A Closer Investigation,'' Spatial Statistics, 7, 1-20.

  • De Oliveira, V. (2013), ``Hierarchical Poisson Models for Spatial Count Data," Journal of Multivariate Analysis, 122, 393-408.

  • Raut, S.S., Jana, A., De Oliveira, V., Muluk, S.C. and Finol, E.A. (2013), "The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics," Journal of Biomechanical Engineering, 135(8), 081010.

  • Ecker, M.D., De Oliveira, V. and Isakson, H. (2013), "A Note on a Non-stationary Point Source Spatial Model," Environmental and Ecological Statistics, 20, 59-67.

  • De Oliveira, V. (2012), "Bayesian Analysis of Conditional Autoregressive Models," Annals of the Institute of Statistical Mathematics, 64, 107-133.

  • Song, J.J. and De Oliveira, V. (2012), "Bayesian Model Selection in Spatial Lattice Models," Statistical Methodology, 9, 228-238.

  • De Oliveira, V. and Ferreira, M.A.R. (2011), "Maximum Likelihood and Restricted Maximum Likelihood Inference for a Class of Gaussian Markov Random Fields," Metrika, 74, 167-183.

  • De Oliveira, V. (2010), "Objective Bayesian Analysis for Gaussian Random Fields." In: Frontiers of Statistical Decision Making and Bayesian Analysis---In Honor of James O. Berger, M.-H. Chen, D.K. Dey, P. Muller, D. Sun and K. Ye (eds.), Springer, pp 497-511.

  • De Oliveira, V. and Rui, C. (2009), "On Shortest Prediction Intervals in Log--Gaussian Random Fields," Computational Statistics & Data Analysis, 53, 4345-4357.

  • De Oliveira, V. and Song, J.J. (2008), "Bayesian Analysis of Simultaneous Autoregressive Models," Sankhya, 70-B, 323-350.

  • Ecker, M. and De Oliveira, V. (2008), "Bayesian Spatial Modeling of Housing Prices Subject to a Localized Externality," Communications in Statistics--Theory and Methods , 37, 2066-2078.

  • Rui, C. and De Oliveira, V. (2008), "Point and Block Prediction in Log-Gaussian Random Fields: The Non-constant Mean Case," Journal of Statistical Planning and Inference, 138, 2128-2142.

  • De Oliveira, V. (2007), "Objective Bayesian Analysis of Spatial Data with Measurement Error," The Canadian Journal of Statistics, 35, 283-301.

  • Ferreira, M.A.R. and De Oliveira, V. (2007), "Bayesian Reference Analysis for Gaussian Markov Random Fields," Journal of Multivariate Analysis, 98, 789-812.

  • De Oliveira, V. (2006), "On Optimal Point and Block Prediction in Log-Gaussian Random Fields," Scandinavian Journal of Statistics, 33, 523-540.

  • Paez, M.S., Gamerman, D. and De Oliveira, V. (2005), "Interpolation Performance of a Spatio-temporal Model with Spatially Varying Coefficients: Application to PM_10 Concentrations in Rio de Janeiro," Environmental and Ecological Statistics, 12, 169-193.

  • De Oliveira, V. (2005), "Bayesian Inference and Prediction of Gaussian Random Fields Based on Censored Data," Journal of Computational and Graphical Statistics, 14, 95-115.

  • De Oliveira, V. (2004), "A Simple Model for Spatial Rainfall Fields," Stochastic Environmental Research and Risk Assessment, 18, 131-140.

  • De Oliveira, V. (2003), "A Note On the Correlation Structure of Transformed Gaussian Random Fields," Australian and New Zealand Journal of Statistics, 45, 353-366.

  • De Oliveira, V., Fokianos, K. and Kedem, B. (2002), "Bayesian Transformed Gaussian Random Field: A Review," Japanese Journal of Applied Statistics, 31, 175-187.

  • De Oliveira, V. and Ecker, M.D. (2002), "Bayesian Hot Spot Detection in the Presence of a Spatial Trend: Application to Total Nitrogen Concentration in the Chesapeake Bay," Environmetrics, 13, 85-101.

  • Berger, J.O., De Oliveira, V. and Sanso, B. (2001), "Objective Bayesian Analysis of Spatially Correlated Data," Journal of the American Statistical Association, 96, 1361-1374.

  • De Oliveira, V. (2000), "Bayesian Prediction of Clipped Gaussian Random Fields," Computational Statistics & Data Analysis, 34, 299-314.

  • Holland D.M., De Oliveira, V., Cox, L.H. and Smith, R.L. (2000), "Estimation of Regional Trends in Sulfur Dioxide Over the Eastern United States," Environmetrics, 11, 373-393.

  • De Oliveira, V., Kedem, B. and Short, D.A. (1997), "Bayesian Prediction of Transformed Gaussian Random Fields," Journal of the American Statistical Association, 92, 1422-1433.

    • TECHNICAL REPORTS

  • De Oliveira, V. and Ecker, M. (2016), "A Non-Stationary Non-Gaussian Hedonic Spatial Model for House Selling Prices."

  • Bindel, D., De Oliveira, V. and Kedem, B. (1997), "An Implementation of the Bayesian Transformed Gaussian Spatial Prediction Model."