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 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 
Emily L. KangUniversity of CincinnatiZweryfikowany adres z ucmail.uc.edu
