Analyzing stochastic computer models: A review with opportunities E Baker, P Barbillon, A Fadikar, RB Gramacy, R Herbei, D Higdon, ... Statistical Science 37 (1), 64-89, 2022 | 43 | 2022 |
A fused Gaussian process model for very large spatial data P Ma, EL Kang Journal of Computational and Graphical Statistics 29 (3), 479-489, 2020 | 37 | 2020 |
Spatio-temporal data fusion for massive sea surface temperature data from MODIS and AMSR-E instruments P Ma, EL Kang Environmetrics, 2019 | 20 | 2019 |
Computer model emulation with high-dimensional functional output in large-scale observing system uncertainty experiments P Ma, A Mondal, BA Konomi, J Hobbs, JJ Song, EL Kang Technometrics 64 (1), 65-79, 2022 | 16 | 2022 |
Multifidelity Computer Model Emulation with High-Dimensional Output: An Application to Storm Surge P Ma, G Karagiannis, BA Konomi, TG Asher, GR Toro, AT Cox Journal of the Royal Statistical Society: Series C 71 (4), 861-883, 2022 | 14 | 2022 |
Beyond Matérn: On A Class of Interpretable Confluent Hypergeometric Covariance Functions P Ma, A Bhadra Journal of the American Statistical Association, 2022 | 13* | 2022 |
Spatial statistical downscaling for constructing high-resolution nature runs in global observing system simulation experiments P Ma, EL Kang, AJ Braverman, HM Nguyen Technometrics 61 (3), 322-340, 2019 | 11 | 2019 |
An additive approximate Gaussian process model for large spatio‐temporal data P Ma, BA Konomi, EL Kang Environmetrics, 2019 | 9 | 2019 |
Ecosystem responses to elevated using airborne remote sensing at Mammoth Mountain, California K Cawse-Nicholson, JB Fisher, CA Famiglietti, A Braverman, ... Biogeosciences 15 (24), 7403-7418, 2018 | 9 | 2018 |
Objective Bayesian analysis of a cokriging model for hierarchical multifidelity codes P Ma SIAM/ASA Journal on Uncertainty Quantification 8 (4), 1358-1382, 2020 | 7 | 2020 |
Computationally efficient nonstationary nearest‐neighbor Gaussian process models using data‐driven techniques BA Konomi, AA Hanandeh, P Ma, EL Kang Environmetrics, 2019 | 6 | 2019 |
ARCokrig: Autoregressive Cokriging Models for Multifidelity Codes P Ma R package version 0.1.2. https://CRAN.R-project.org/package=ARCokrig, 2021 | 2* | 2021 |
GPBayes: Tools for Gaussian Process Modeling in Uncertainty Quantification P Ma R package version 0.1.0-3. https://CRAN.R-project.org/package=GPBayes., 2021 | | 2021 |
Addressing Needs in Observed and Simulated Storm Surge Data for Uncertainty Quantification T Asher, R Luettich, JL Irish, P Ma, M Bensi, D Resio Ocean Sciences Meeting 2020, 2020 | | 2020 |
Uncertainty Quantification in Assessing Storm Surge Hazards P Ma, JO Berger, T Asher AGU Fall Meeting Abstracts 2019, NH31E-0883, 2019 | | 2019 |
Hierarchical Additive Spatial and Spatio-Temporal Process Models for Massive Datasets P Ma University of Cincinnati, 2018 | | 2018 |
Data fusion and spatial inference for remote sensing V Yadav, T Stough, N Cressie, A Michalak, P Ma, M Katzfuss, E Kang, ... Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space …, 2017 | | 2017 |
NCAR Technical Notes NCAR/TN-530+ STR W Kaufman, P Ma, D Hammerling, D Lombardozzi | | 2016 |