Montserrat Fuentes Sharma, A., Guinness, J., Muyskens, A., Polizzotto, M. L., Fuentes, M., & Hesterberg, D. (2022).

Spatial statistical modeling of arsenic accumulation in microsites of diverse soils

. GEODERMA, 411. https://doi.org/10.1016/j.geoderma.2022.115697 Muyskens, A., Guinness, J., & Fuentes, M. (2022, April 4). Partition-Bas'd Nonstationary Covariance Estimation Using the Stochastic Score Approximation. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS. https://doi.org/10.1080/10618600.2022.2044830 Jhuang, A.-T., Fuentes, M., Bandyopadhyay, D., & Reich, B. J. (2020). Spatiotemporal signal detection using continuous shrinkage priors. STATISTICS IN MEDICINE, 39(13), 1817–1832. https://doi.org/10.1002/sim.8514 Rekabdarkolaee, H. M., Krut, C., Fuentes, M., & Reich, B. J. (2019). A Bayesian multivariate functional model with spatially varying coefficient approach for modeling hurricane track data. SPATIAL STATISTICS, 29, 351–365. https://doi.org/10.1016/j.spasta.2018.12.006 Huang, Y.-N., Reich, B. J., Fuentes, M., & Sankarasubramanian, A. (2019). Complete spatial model calibration. The Annals of Applied Statistics, 13(2), 746–766. https://doi.org/10.1214/18-AOAS1219 Sharma, A., Muyskens, A., Guinness, J., Polizzotto, M. L., Fuentes, M., Tappero, R. V., … Hesterberg, D. (2019). Multi-element effects on arsenate accumulation in a geochemical matrix determined using mu-XRF, mu-XANES and spatial statistics. JOURNAL OF SYNCHROTRON RADIATION, 26, 1967–1979. https://doi.org/10.1107/S1600577519012785 Jhuang, A.-T., Fuentes, M., Jones, J. L., Esteves, G., Fancher, C. M., Furman, M., & Reich, B. J. (2019). Spatial Signal Detection Using Continuous Shrinkage Priors. TECHNOMETRICS, 61(4), 494–506. https://doi.org/10.1080/00401706.2018.1546622 Terres, M. A., Fuentes, M., Hesterberg, D., & Polizzotto, M. (2018). Bayesian Spectral Modeling for Multivariate Spatial Distributions of Elemental Concentrations in Soil. BAYESIAN ANALYSIS, 13(1), 1–28. https://doi.org/10.1214/16-ba1034 Cunha, M., Gamerman, D., Fuentes, M., & Paez, M. (2017). A non-stationary spatial model for temperature interpolation applied to the state of Rio de Janeiro. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 66(5), 919–939. https://doi.org/10.1111/rssc.12207 Miao, G., Noormets, A., Domec, J.-C., Fuentes, M., Trettin, C. C., Sun, G., … King, J. S. (2017). Hydrology and microtopography control carbon dynamics in wetlands: Implications in partitioning ecosystem respiration in a coastal plain forested wetland. AGRICULTURAL AND FOREST METEOROLOGY, 247, 343–355. https://doi.org/10.1016/j.agrformet.2017.08.022 Warren, J. L., Stingone, J. A., Herring, A. H., Luben, T. J., Fuentes, M., Aylsworth, A. S., … Olshan, A. F. (2016). Bayesian multinomial probit modeling of daily windows of susceptibility for maternal PM2.5 exposure and congenital heart defects. STATISTICS IN MEDICINE, 35(16), 2786–2801. https://doi.org/10.1002/sim.6891 Mannshardt, E., Sucic, K., Fuentes, M., & Bingham, F. M. (2016). Comparison of Distributional Statistics of Aquarius and Argo Sea Surface Salinity Measurements. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 33(1), 103–118. https://doi.org/10.1175/jtech-d-15-0068.1 Sun, Y., Wang, H. J., & Fuentes, M. (2016). Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation. TECHNOMETRICS, 58(1), 127–137. https://doi.org/10.1080/00401706.2015.1017115 Shivkumar, A. P., Wang-Li, L., Shah, S. B., Stikeleather, L. F., & Fuentes, M. (2016). Performance analysis of a poultry engineering chamber complex for animal environment, air quality, and welfare studies. Transactions of the ASABE, 59(5), 1371–1382. Warren, J. L., Fuentes, M., Herring, A. H., & Langlois, P. H. (2016). Spatiotemporal modeling of preterm birth. Handbook of Spatial Epidemiology, 649–663. Guinness, J., & Fuentes, M. (2015). Likelihood approximations for big nonstationary spatial temporal lattice data. Statistica Sinica, 25(1), 329–349. Smith, L. B., Reich, B. J., Herring, A. H., Langlois, P. H., & Fuentes, M. (2015). Multilevel quantile function modeling with application to birth outcomes. BIOMETRICS, 71(2), 508–519. https://doi.org/10.1111/biom.12294 Smith, L. B., Fuentes, M., Gordon-Larsen, P., & Reich, B. J. (2015). QUANTILE REGRESSION FOR MIXED MODELS WITH AN APPLICATION TO EXAMINE BLOOD PRESSURE TRENDS IN CHINA. ANNALS OF APPLIED STATISTICS, 9(3), 1226–1246. https://doi.org/10.1214/15-aoas841 Reich, B. J., & Fuentes, M. (2015). Spatial Bayesian Nonparametric Methods. NONPARAMETRIC BAYESIAN INFERENCE IN BIOSTATISTICS, pp. 347–357. https://doi.org/10.1007/978-3-319-19518-6_17 Vock, L. F. B., Reich, B. J., Fuentes, M., & Dominici, F. (2015). Spatial Variable Selection Methods for Investigating Acute Health Effects of Fine Particulate Matter Components. BIOMETRICS, 71(1), 167–177. https://doi.org/10.1111/biom.12254 Stingone, J. A., Luben, T. J., Daniels, J. L., Fuentes, M., Richardson, D. B., Aylsworth, A. S., … Olshan, A. F. (2014). Maternal Exposure to Criteria Air Pollutants and Congenital Heart Defects in Offspring: Results from the National Birth Defects Prevention Study. ENVIRONMENTAL HEALTH PERSPECTIVES, 122(8), 863–872. https://doi.org/10.1289/ehp.1307289 Mannshardt, E., Sucic, K., Jiao, W., Dominici, F., Frey, H. C., Reich, B., & Fuentes, M. (2013). Comparing exposure metrics for the effects of fine particulate matter on emergency hospital admissions. JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY, 23(6), 627–636. https://doi.org/10.1038/jes.2013.39 Fuentes, M., & Reich, B. (2013). Multivariate spatial nonparametric modelling via kernel processes mixing. Statistica Sinica, 23(1), 75–97. Fuentes, M., Henry, J., & Reich, B. (2013). Nonparametric spatial models for extremes: application to extreme temperature data. EXTREMES, 16(1), 75–101. https://doi.org/10.1007/s10687-012-0154-1 Warren, J., Fuentes, M., Herring, A., & Langlois, P. (2012). Bayesian spatial-temporal model for cardiac congenital anomalies and ambient air pollution risk assessment. ENVIRONMETRICS, 23(8), 673–684. https://doi.org/10.1002/env.2174 Modlin, D., Fuentes, M., & Reich, B. (2012). Circular conditional autoregressive modeling of vector fields. ENVIRONMETRICS, 23(1), 46–53. https://doi.org/10.1002/env.1133 Zhou, J., Chang, H. H., & Fuentes, M. (2012). Estimating the Health Impact of Climate Change With Calibrated Climate Model Output. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 17(3), 377–394. https://doi.org/10.1007/s13253-012-0105-y Reich, B. J., & Fuentes, M. (2012). Nonparametric Bayesian models for a spatial covariance. STATISTICAL METHODOLOGY, 9(1-2), 265–274. https://doi.org/10.1016/j.stamet.2011.01.007 Warren, J., Fuentes, M., Herring, A., & Langlois, P. (2012). Spatial-Temporal Modeling of the Association between Air Pollution Exposure and Preterm Birth: Identifying Critical Windows of Exposure. BIOMETRICS, 68(4), 1157–1167. https://doi.org/10.1111/j.1541-0420.2012.01774.x Chang, H. H., Fuentes, M., & Frey, H. C. (2012). Time series analysis of personal exposure to ambient air pollution and mortality using an exposure simulator. JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY, 22(5), 483–488. https://doi.org/10.1038/jes.2012.53 Reich, B. J., Kalendra, E., Storlie, C. B., Bondell, H. D., & Fuentes, M. (2012). Variable selection for high dimensional Bayesian density estimation: application to human exposure simulation. Journal of the Royal Statistical Society. Series C, Applied Statistics, 61, 47–66. Reich, B. J., Fuentes, M., & Dunson, D. B. (2011). Bayesian Spatial Quantile Regression. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 106(493), 6–20. https://doi.org/10.1198/jasa.2010.ap09237 Zhou, J., Fuentes, M., & Davis, J. (2011). Calibration of Numerical Model Output Using Nonparametric Spatial Density Functions. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 16(4), 531–553. https://doi.org/10.1007/s13253-011-0076-4 Dennis, R., Fox, T., Fuentes, M., Gilliland, A., Hanna, S., Hogrefe, C., … Venkatram, A. (2010). A framework for evaluating regional-scale numerical photochemical modeling systems. ENVIRONMENTAL FLUID MECHANICS, 10(4), 471–489. https://doi.org/10.1007/s10652-009-9163-2 Reich, B. J., Fuentes, M., Herring, A. H., & Evenson, K. R. (2010). Bayesian Variable Selection for Multivariate Spatially Varying Coefficient Regression. BIOMETRICS, 66(3), 772–782. https://doi.org/10.1111/j.1541-0420.2009.01333.x Chang, H. H., Zhou, J. W., & Fuentes, M. (2010). Impact of climate change on ambient ozone level and mortality in Southeastern United States. International Journal of Environmental Research and Public Health, 7(7), 2866–2880. Reich, B. J., Fuentes, M., & Burke, J. (2009). Analysis of the effects of ultrafine particulate matter while accounting for human exposure. ENVIRONMETRICS, 20(2), 131–146. https://doi.org/10.1002/env.915 Choi, J., Fuentes, M., & Reich, B. J. (2009). Spatial-temporal association between fine particulate matter and daily mortality. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 53(8), 2989–3000. https://doi.org/10.1016/j.csda.2008.05.018 Fuentes, M., Chen, L., & Davis, J. M. (2008). A class of nonseparable and nonstationary spatial temporal covariance functions. ENVIRONMETRICS, 19(5), 487–507. https://doi.org/10.1002/env.891 Song, H.-R., Fuentes, M., & Ghosh, S. (2008). A comparative study of Gaussian geostatistical models and Gaussian Markov random field models. JOURNAL OF MULTIVARIATE ANALYSIS, 99(8), 1681–1697. https://doi.org/10.1016/j.jmva.2008.01.012 Foley, K. M., & Fuentes, M. (2008). A statistical framework to combine multivariate spatial data and physical models for hurricane surface wind prediction. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 13(1), 37–59. https://doi.org/10.1198/108571108X276473 Fuentes, M. (2008, August). Comments on: Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds. TEST, Vol. 17, pp. 245–248. https://doi.org/10.1007/s11749-008-0119-5 Fuentes, M., Reich, B., & Lee, G. (2008). SPATIAL-TEMPORAL MESOSCALE MODELING OF RAINFALL INTENSITY USING GAGE AND RADAR DATA. ANNALS OF APPLIED STATISTICS, 2(4), 1148–1169. https://doi.org/10.1214/08-AOAS166 Fuentes, M., Guttorp, P., & Stein, M. L. (2008). SPECIAL SECTION ON STATISTICS IN THE ATMOSPHERIC SCIENCES. ANNALS OF APPLIED STATISTICS, 2(4), 1143–1147. https://doi.org/10.1214/08-AOAS209 Park, M. S., & Fuentes, M. (2008). Testing lack of symmetry in spatial-temporal processes. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 138(10), 2847–2866. https://doi.org/10.1016/j.jspi.2007.10.021 Reich, B. J., & Fuentes, M. (2007). A MULTIVARIATE SEMIPARAMETRIC BAYESIAN SPATIAL MODELING FRAMEWORK FOR HURRICANE SURFACE WIND FIELDS. ANNALS OF APPLIED STATISTICS, 1(1), 249–264. https://doi.org/10.1214/07-AOAS108 Fuentes, M. (2007). Approximate likelihood for large irregularly spaced spatial data. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 102(477), 321–331. https://doi.org/10.1198/016214506000000852 Fuentes, M., Chaudhuri, A., & Holland, D. M. (2007). Bayesian entropy for spatial sampling design of environmental data. ENVIRONMENTAL AND ECOLOGICAL STATISTICS, 14(3), 323–340. https://doi.org/10.1007/s10651-007-0017-0 Xie, L., Bao, S. W., Pietrafesa, L. J., Foley, K., & Fuentes, M. (2006). A real-time hurricane surface wind forecasting model: Formulation and verification. MONTHLY WEATHER REVIEW, 134(5), 1355–1370. https://doi.org/10.1175/MWR3126.1 Fuentes, M., Kittel, T. G. F., & Nychka, D. (2006). Sensitivity of ecological models to their climate drivers: Statistical ensembles for forcing. ECOLOGICAL APPLICATIONS, 16(1), 99–116. https://doi.org/10.1890/04-1157 Fuentes, M., Song, H.-R., Ghosh, S. K., Holland, D. M., & Davis, J. M. (2006). Spatial association between speciated fine particles and mortality. BIOMETRICS, 62(3), 855–863. https://doi.org/10.1111/j.1541-0420.2006.00526.x Fuentes, M. (2006). Testing for separability of spatial-temporal covariance functions. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 136(2), 447–466. https://doi.org/10.1016/j.jspi.2004.07.004 Flores, F. J., Allen, H. L., Cheshire, H. M., Davis, J. M., Fuentes, M., & Kelting, D. (2006). Using multispectral satellite imagery to estimate leaf area and response to silvicultural treatments in loblolly pine stands. CANADIAN JOURNAL OF FOREST RESEARCH-REVUE CANADIENNE DE RECHERCHE FORESTIERE, 36(6), 1587–1596. https://doi.org/10.1139/X06-030 Fuentes, M. (2005). A formal test for nonstationarity of spatial stochastic processes. JOURNAL OF MULTIVARIATE ANALYSIS, 96(1), 30–54. https://doi.org/10.1016/j.jmva.2004.09.003 Fuentes, M., & Raftery, A. E. (2005). Model evaluation and spatial interpolation by Bayesian combination of observations with outputs from numerical models. BIOMETRICS, 61(1), 36–45. https://doi.org/10.1111/j.0006-341X.2005.030821.x Fuentes, M., Chen, L., Davis, J. M., & Lackmann, G. M. (2005, August). Modeling and predicting complex space-time structures and patterns of coastal wind fields. ENVIRONMETRICS, Vol. 16, pp. 449–464. https://doi.org/10.1002/env.714 Fuentes, M., & Boos, D. D. (2005, August). Special issue - Environmental and health statistics. ENVIRONMETRICS, Vol. 16, pp. 421–421. https://doi.org/10.1002/env.711 Fuentes, M., Higdon, D., Sanso, B., Gelfand, A. E., Schmidt, A. M., Banerjee, S., & Sirmans, C. F. (2004). Nonstationary multivariate process modeling through spatially varying coregionalization - Discussion. TEST, 13(2), 295–312. Yuen, D. A., Erlebacher, G., Vasilyev, O. V., Goldstein, D. E., & Fuentes, M. (2004, December). Role of wavelets in the physical and statistical modelling of complex geological processes. PURE AND APPLIED GEOPHYSICS, Vol. 161, pp. 2231–2244. https://doi.org/10.1007/s00024-004-2560-z Doney, S. C., Glover, D. M., Mccue, S. J., & Fuentes, M. (2003). Mesoscale variability of Sea-viewing Wide Field-of-view Sensor(SeaWiFS) satellite ocean color: Global patterns and spatial scales. Journal of Geophysical Research. Oceans, 108(C2), 3024–3021. Mateu, J., Montes, F., & Fuentes, M. (2003). Recent advances in space-time statistics with applications to environmental data: An overview. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 108(D24). https://doi.org/10.1029/2003jd003819 Fuentes, M. (2003). Statistical assessment of geographic areas of compliance with air quality standards. Journal of Geophysical Research. Atmospheres, 108(D24). Fuentes, M., Guttorp, P., & Challenor, P. (2003). Statistical assessment of numerical models. International Statistical Review, 71(2), 201–221. Fuentes, M. (2002). Spectral methods for nonstationary spatial processes. BIOMETRIKA, 89(1), 197–210. https://doi.org/10.1093/biomet/89.1.197 Fuentes, M. (2001). A high frequency kriging approach for non-stationary environmental processes. Environmetrics, 12(5), 469–483. https://doi.org/10.1002/env.473 Fuentes, M. (2001). Fixed-domain asymptotics for variograms using subsampling. MATHEMATICAL GEOLOGY, 33(6), 679–691. https://doi.org/10.1023/A:1011074615343 Fuentes, M. (2000). Predicting integrals of diffusion processes. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 90(2), 183–193. https://doi.org/10.1016/S0378-3758(00)00121-X Smith, R. L., Spitzner, D., Kim, Y., & Fuentes, M. (2000, August). Threshold dependence of mortality effects for fine and coarse particles in Phoenix, Arizona. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION, Vol. 50, pp. 1367–1379. https://doi.org/10.1080/10473289.2000.10464172