Works matching AU Reich, Brian
Results: 129
False discovery control in large-scale spatial multiple testing.
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- Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2015, v. 77, n. 1, p. 59, doi. 10.1111/rssb.12064
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Partially supervised spatiotemporal clustering for burglary crime series identification.
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- Journal of the Royal Statistical Society: Series A (Statistics in Society), 2015, v. 178, n. 2, p. 465, doi. 10.1111/rssa.12076
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Landscape‐level variation in Bt crops predict Helicoverpa zea (Lepidoptera: Noctuidae) resistance in cotton agroecosystems.
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- Pest Management Science, 2021, v. 77, n. 12, p. 5454, doi. 10.1002/ps.6585
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- Article
Spatial regression with an informatively missing covariate: Application to mapping fine particulate matter.
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- Environmetrics, 2018, v. 29, n. 4, p. 1, doi. 10.1002/env.2499
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- Article
Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland
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- Environmetrics, 2012, v. 23, n. 8, p. 638, doi. 10.1002/env.2178
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Circular conditional autoregressive modeling of vector fields.
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- Environmetrics, 2012, v. 23, n. 1, p. 46, doi. 10.1002/env.1133
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Analysis of the effects of ultrafine particulate matter while accounting for human exposure.
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- Environmetrics, 2009, v. 20, n. 2, p. 131, doi. 10.1002/env.915
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Spatial prediction of crystalline defects observed in molecular dynamic simulations of plastic damage.
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- Journal of Applied Statistics, 2017, v. 44, n. 10, p. 1761, doi. 10.1080/02664763.2016.1221915
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Multiple window discrete scan statistic for higher-order Markovian sequences.
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- Journal of Applied Statistics, 2015, v. 42, n. 8, p. 1690, doi. 10.1080/02664763.2015.1005061
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Multisensor fusion of remotely sensed vegetation indices using space‐time dynamic linear models.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2021, v. 70, n. 3, p. 793, doi. 10.1111/rssc.12495
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- Article
Global forensic geolocation with deep neural networks.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2020, v. 69, n. 4, p. 909, doi. 10.1111/rssc.12427
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- Article
Optimal treatment allocations in space and time for on‐line control of an emerging infectious disease.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2018, v. 67, n. 4, p. 743, doi. 10.1111/rssc.12266
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- Article
A marginal cure rate proportional hazards model for spatial survival data.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2015, v. 64, n. 4, p. 673, doi. 10.1111/rssc.12098
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- Article
A spatial time-to-event approach for estimating associations between air pollution and preterm birth.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2013, v. 62, n. 2, p. 167, doi. 10.1111/j.1467-9876.2012.01056.x
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Spatiotemporal quantile regression for detecting distributional changes in environmental processes.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2012, v. 61, n. 4, p. 535, doi. 10.1111/j.1467-9876.2011.01025.x
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- Article
Variable selection for high dimensional Bayesian density estimation: application to human exposure simulation.
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- Journal of the Royal Statistical Society: Series C (Applied Statistics), 2012, v. 61, n. 1, p. 47, doi. 10.1111/j.1467-9876.2011.00772.x
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- Article
The recent past and promising future for data integration methods to estimate species' distributions.
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- Methods in Ecology & Evolution, 2019, v. 10, n. 1, p. 22, doi. 10.1111/2041-210X.13110
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- Article
Integrating auxiliary data in optimal spatial design for species distribution modelling.
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- Methods in Ecology & Evolution, 2018, v. 9, n. 6, p. 1626, doi. 10.1111/2041-210X.13002
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- Article
Occupancy estimation for rare species using a spatially adaptive sampling design.
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- Methods in Ecology & Evolution, 2016, v. 7, n. 3, p. 285, doi. 10.1111/2041-210X.12499
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- Article
DEEPKRIGING: SPATIALLY DEPENDENT DEEP NEURAL NETWORKS FOR SPATIAL PREDICTION.
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- Statistica Sinica, 2024, v. 34, n. 1, p. 291, doi. 10.5705/ss.202021.0277
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- Article
A BAYESIAN SEMI-PARAMETRIC MIXTURE MODEL FOR BIVARIATE EXTREME VALUE ANALYSIS WITH APPLICATION TO PRECIPITATION FORECASTING.
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- Statistica Sinica, 2021, v. 31, n. 3, p. 1619, doi. 10.5705/ss.202018.0420
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- Article
A Multiresolution Approach to Estimating the Value Added by Regional Climate Models.
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- Journal of Climate, 2015, v. 28, n. 22, p. 8873, doi. 10.1175/JCLI-D-14-00557.1
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- Article
Retracted: Multi‐model penalized regression.
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- Statistical Analysis & Data Mining, 2021, v. 14, n. 6, p. 698, doi. 10.1002/sam.11496
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- Article
A Bayesian mixture model for clustering and selection of feature occurrence rates under mean constraints.
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- Statistical Analysis & Data Mining, 2017, v. 10, n. 6, p. 393, doi. 10.1002/sam.11350
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- Article
Occupancy and Abundance of Eleutherodactylus Frogs in Coffee Plantations in Puerto Rico.
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- Herpetologica, 2017, v. 73, n. 4, p. 297, doi. 10.1655/Herpetologica-D-16-00089
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Associations between flood risk and US Census tract–level health outcomes.
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- American Journal of Epidemiology, 2024, v. 193, n. 10, p. 1384, doi. 10.1093/aje/kwae093
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Modeling Climate Change Effects on the Height Growth of Loblolly Pine.
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- Forest Science, 2015, v. 61, n. 4, p. 703, doi. 10.5849/forsci.14-075
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- Article
Modeling Climate Change Effects on the Height Growth of Loblolly Pine.
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- Forest Science, 2015, v. 61, n. 4, p. 703, doi. 10.5849/forsci.14-075
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- Article
SPARSE BAYESIAN ADDITIVE NONPARAMETRIC REGRESSION WITH APPLICATION TO HEALTH EFFECTS OF PESTICIDES MIXTURES.
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- Statistica Sinica, 2020, v. 30, n. 1, p. 55, doi. 10.5705/ss.202017.0315
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- Article
A TEST FOR ISOTROPY ON A SPHERE USING SPHERICAL HARMONIC FUNCTIONS.
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- Statistica Sinica, 2019, v. 29, n. 3, p. 1253, doi. 10.5705/ss.202017.0475
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Reanalysis of PFO5DoA Levels in Blood from Wilmington, North Carolina, Residents, 2017-2018.
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- Environmental Health Perspectives, 2024, v. 132, n. 2, p. 027701-1, doi. 10.1289/EHP13339
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Measurement of Hydro-EVE and 6:2 FTS in Blood from Wilmington, North Carolina, Residents, 2017-2018.
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- Environmental Health Perspectives, 2024, v. 132, n. 2, p. 027702-1, doi. 10.1289/EHP14503
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- Article
HOW FREQUENTLY WILL FLOODS OCCUR?
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- Journal of the American Water Resources Association, 1973, v. 9, n. 1, p. 187, doi. 10.1111/j.1752-1688.1973.tb01724.x
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SEASONAL OCCURRENCE OF ANNUAL FLOODS ON SMALL PENNSYLVANIA WATERSHEDS.
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- Journal of the American Water Resources Association, 1971, v. 7, n. 6, p. 1153, doi. 10.1111/j.1752-1688.1971.tb05053.x
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Accounting for Location Measurement Error in Imaging Data With Application to Atomic Resolution Images of Crystalline Materials.
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- Technometrics, 2022, v. 64, n. 1, p. 103, doi. 10.1080/00401706.2021.1905070
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- Article
Sequential Optimization in Locally Important Dimensions.
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- Technometrics, 2021, v. 63, n. 2, p. 236, doi. 10.1080/00401706.2020.1714738
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- Article
Spatial Signal Detection Using Continuous Shrinkage Priors.
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- Technometrics, 2019, v. 61, n. 4, p. 494, doi. 10.1080/00401706.2018.1546622
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- Article
Malware Detection Using Nonparametric Bayesian Clustering and Classification Techniques.
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- Technometrics, 2015, v. 57, n. 4, p. 535, doi. 10.1080/00401706.2014.958916
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- Article
Modeling wildland fire burn severity in California using a spatial Super Learner approach.
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- Environmental & Ecological Statistics, 2024, v. 31, n. 2, p. 387, doi. 10.1007/s10651-024-00601-1
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- Article
Correction: Nonparametric conditional density estimation in a deep learning framework for short-term forecasting.
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- 2022
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- Correction Notice
Nonparametric conditional density estimation in a deep learning framework for short-term forecasting.
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- Environmental & Ecological Statistics, 2022, v. 29, n. 4, p. 677, doi. 10.1007/s10651-021-00499-z
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- Article
A spatial model for rare binary events.
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- Environmental & Ecological Statistics, 2017, v. 24, n. 4, p. 485, doi. 10.1007/s10651-017-0385-z
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- Article
Spatial regression modeling via the R2D2 framework.
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- Environmetrics, 2024, v. 35, n. 2, p. 1, doi. 10.1002/env.2829
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- Article
Estimating atmospheric motion winds from satellite image data using space‐time drift models.
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- Environmetrics, 2023, v. 34, n. 8, p. 1, doi. 10.1002/env.2818
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- Article
Statistical analysis of multi‐day solar irradiance using a threshold time series model.
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- Environmetrics, 2022, v. 33, n. 3, p. 1, doi. 10.1002/env.2716
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- Article
Bayesian variable selection for high‐dimensional rank data.
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- Environmetrics, 2021, v. 32, n. 7, p. 1, doi. 10.1002/env.2682
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A multivariate spatial skew‐t process for joint modeling of extreme precipitation indexes.
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- Environmetrics, 2020, v. 31, n. 3, p. 1, doi. 10.1002/env.2602
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- Article
Fungi Identify the Geographic Origin of Dust Samples.
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- PLoS ONE, 2015, v. 10, n. 4, p. 1, doi. 10.1371/journal.pone.0122605
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A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes.
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- International Journal of Environmental Research & Public Health, 2017, v. 14, n. 9, p. 1046, doi. 10.3390/ijerph14091046
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- Article
Flood Series Compared to Rainfall Extremes.
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- Water Resources Research, 1970, v. 6, n. 6, p. 1655, doi. 10.1029/WR006i006p01655
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- Article