Joseph Guinness

Sahoo, I., Guinness, J., & Reich, B. J. J. (2023, July 6). Estimating atmospheric motion winds from satellite image data using space-time drift models. ENVIRONMETRICS, Vol. 7. https://doi.org/10.1002/env.2818

Sharma, A., Guinness, J., Muyskens, A., Polizzotto, M. L., Fuentes, M., & Hesterberg, D. (2022). <p>Spatial statistical modeling of arsenic accumulation in microsites of diverse soils</p>. GEODERMA, 411. https://doi.org/10.1016/j.geoderma.2022.115697

Lan, Z., Reich, B. J., Guinness, J., Bandyopadhyay, D., Ma, L., & Moeller, F. G. (2022). Geostatistical modeling of positive-definite matrices: An application to diffusion tensor imaging. BIOMETRICS, 78(2), 548–559. https://doi.org/10.1111/biom.13445

Roy, A., Reich, B. J., Guinness, J., Shinohara, R. T., & Staicu, A.-M. (2021, June 16). Spatial Shrinkage Via the Product Independent Gaussian Process Prior. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, Vol. 6. https://doi.org/10.1080/10618600.2021.1923512

Brantley, H. L., Guinness, J., & Chi, E. C. (2020). BASELINE DRIFT ESTIMATION FOR AIR QUALITY DATA USING QUANTILE TREND FILTERING. ANNALS OF APPLIED STATISTICS, 14(2), 585–604. https://doi.org/10.1214/19-AOAS1318

Sahoo, I., Guinness, J., & Reich, B. J. (2019). A TEST FOR ISOTROPY ON A SPHERE USING SPHERICAL HARMONIC FUNCTIONS. STATISTICA SINICA, 29(3), 1253–1276. https://doi.org/10.5705/ss.202017.0475

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

Guinness, J., & Hammerling, D. (2018). Compression and Conditional Emulation of Climate Model Output. Journal of the American Statistical Association, 113(521), 56–67. https://doi.org/10.1080/01621459.2017.1395339

Reich, B. J., Guinness, J., Vandekar, S. N., Shinohara, R. T., & Staicu, A.-M. (2018). Fully Bayesian spectral methods for imaging data. BIOMETRICS, 74(2), 645–652. https://doi.org/10.1111/biom.12782

Guinness, J. (2018). Permutation and Grouping Methods for Sharpening Gaussian Process Approximations. TECHNOMETRICS, 60(4), 415–429. https://doi.org/10.1080/00401706.2018.1437476

Matli, V. R. R., Fang, S., Guinness, J., Rabalais, N. N., Craig, J. K., & Obenour, D. R. (2018). Space-Time Geostatistical Assessment of Hypoxia in the Northern Gulf of Mexico. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 52(21), 12484–12493. https://doi.org/10.1021/acs.est.8b03474

Castruccio, S., & Guinness, J. (2017). An evolutionary spectrum approach to incorporate large-scale geographical descriptors on global processes. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 66(2), 329–344. https://doi.org/10.1111/rssc.12167

Guinness, J., & Fuentes, M. (2017). Circulant Embedding of Approximate Covariances for Inference From Gaussian Data on Large Lattices. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 26(1), 88–97. https://doi.org/10.1080/10618600.2016.1164534

Farjat, A., Reich, B. J., Guinness, J., Whetten, R., McKeand, S., & Isik, F. (2017). Optimal Seed Deployment Under Climate Change Using Spatial Models: Application to Loblolly Pine in the Southeastern US. Journal of the American Statistical Association, 112(519), 909–920. https://doi.org/10.1080/01621459.2017.1292179

Guinness, J., & Fuentes, M. (2016). Isotropic covariance functions on spheres: Some properties and modeling considerations. Journal of Multivariate Analysis, 143, 143–152. https://doi.org/10.1016/J.JMVA.2015.08.018

Guinness, J., & Fuentes, M. (2015). Likelihood approximations for big nonstationary spatial temporal lattice data. Statistica Sinica, 25(1), 329–349.

Guinness, J., Fuentes, M., Hesterberg, D., & Polizzotto, M. (2014). Multivariate spatial modeling of conditional dependence in microscale soil elemental composition data. Spatial Statistics, 9(C), 93–108. https://doi.org/10.1016/J.SPASTA.2014.03.009

Guinness, J., & Stein, M. L. (2013). INTERPOLATION OF NONSTATIONARY HIGH FREQUENCY SPATIAL-TEMPORAL TEMPERATURE DATA. ANNALS OF APPLIED STATISTICS, 7(3), 1684–1708. https://doi.org/10.1214/13-aoas633