Peer-reviewed and published papers

  1. Ma, P. and Bhadra, A. (2023) "Beyond Matérn: On A Class of Interpretable Confluent Hypergeometric Covariance Functions." Journal of the American Statistical Association, T&M. 118(543), 2045-2058. DOI:10.1080/01621459.2022.2027775. [arXiv] [JASA]
  2. Ma, P., Karagiannis, G., Konomi, B. A., Asher, T. G., Toro, G. R., and Cox, A. T. (2022) "Multifidelity Computer Model Emulation with High-Dimensional Output: An Application to Storm Surge." Journal of the Royal Statistical Society: Series C. 71(4), 861-883. DOI:10.1111/rssc.12558. [arXiv] [RSSC] [code]
  3. Baker, E., Barbillon, P., Fadikar, A., Gramacy, R. B., Herbei, R., Higdon, D., Huang, J., Johnson, L. R., Ma, P., Mondal, A., Pires, B., Sacks, J., and Sokolov, V. (2022) "Analyzing Stochastic Computer Models: A Review with Opportunities." Statistical Science, 37(1), 64-89. [arXiv] [STS]
  4. Ma, P., Mondal, A., Konomi, B. A., Hobbs, J., Song, J. J., and Kang, E. L. (2021) "Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments." Technometrics. Accepted. DOI:10.1080/00401706.2021.1895890. [arXiv] [TECH] [code]
  5. Ma, P. (2020) "Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes." SIAM/ASA Journal on Uncertainty Quantification, 8(4), 1358-1382. [arXiv] [JUQ] [code]
  6. Ma, P. and Kang, E. L. (2020) "A Fused Gaussian Process Model for Very Large Spatial Data." Journal of Computational and Graphical Statistics, 29(3), 479-489. [arXiv] [JCGS] [code]
      •Early version wins the Student Paper Competition in the 2017 ICSA Applied Statistics Symposium
      •Early version wins the honorable mention in the 2016 Student Paper Competition in the Section on Statistics and the Environment of American Statistical Association
  7. Konomi, B., Hanandeh, A. A., Ma, P., and Kang, E. L. (2019) "Computationally Efficient Nonstationary Nearest Neighbor Gaussian Process Models Using Data-Driven Techniques." Environmetrics, DOI:10.1002/env.2571. [ENV]
  8. Ma, P. and Kang, E. L. (2019) "Spatio-Temporal Data Fusion for Massive Sea Surface Temperature Data from MODIS and AMSR-E Instruments." Environmetrics, DOI:10.1002/env.2594. [arXiv] [ENV]
  9. Ma, P., Konomi, B., and Kang, E. L. (2019) "An Additive Approximate Gaussian Process Model for Large Spatio-Temporal Data." Environmetrics, DOI:10.1002/env.2569. [arXiv] [ENV]
  10. Ma, P., Kang, E. L., Braverman, A., and Nguyen, H. (2019) "Spatial Statistical Downscaling for Constructing High-Resolution Nature Runs in Global Observing System Simulation Experiments." Technometrics, 61(3), 322-340. [arXiv] [TECH] [code]
      •Early version wins the 2018 Student Paper Competition in the Section on Statistics and the Environment of American Statistical Association
  11. Cawse-Nicholson, K., Fisher, J. B., Famiglietti, C. A., Braverman, A., Schwandner, F. M., Lewicki, J. L., Townsend, P. A., Schimel, D. S., Pavlick, R., Bormann, K. J., Ferraz, A., Kang, E. L., Ma, P., Bogue, R. R., Youmans, T., and Pieri, D. C. (2018) "Ecosystem Responses to Elevated CO2 Using Airborne Remote Sensing at Mammoth Mountain, California." Biogeosciences, 15, 7403-7418. [BG]

Technical report

  1. Kaufman, W., Ma, P., Hammerling, D., and Lombardozzi, D. (2016) "Ozone and Foliar Damage Analysis: NCAR and St. Louis." NCAR Technical Note NCAR/TN-530+STR, 31 pp, doi: 10.5072/FK2TX3B723. [PDF]

Statistical software

  1. Ma, P. (2021) R package "GPBayes: Tools for Gaussian Process Modeling in Uncertainty Quantification." [GitHub] [CRAN] CRAN/METACRAN CRAN/METACRAN
  2. Ma, P. (2020) R package "ARCokrig: Autoregressive Cokriging Models for Multifidelity Codes." [GitHub] [CRAN] CRAN/METACRAN CRAN/METACRAN