Artikel dengan mandat akses publik - Douglas NychkaPelajari lebih lanjut
Tidak tersedia di mana pun: 2
A comparison of automated statistical quality control methods for error detection in historical radiosonde temperatures.
AN Anderson, JM Browning, J Comeaux, AS Hering, D Nychka
International Journal of Climatology 36 (1), 2016
Mandat: US National Science Foundation
Spatial analysis in climatology
D Nychka, CK Wikle
Handbook of Environmental and Ecological Statistics, 657-686, 2019
Mandat: US National Science Foundation
Tersedia di suatu tempat: 23
A case study competition among methods for analyzing large spatial data
MJ Heaton, A Datta, AO Finley, R Furrer, J Guinness, R Guhaniyogi, ...
Journal of agricultural, biological and environmental Statistics 24, 398-425, 2019
Mandat: US National Science Foundation, Swiss National Science Foundation, US …
Consistency of modelled and observed temperature trends in the tropical troposphere
BD Santer, PW Thorne, L Haimberger, KE Taylor, TML Wigley, ...
International Journal of Climatology: A Journal of the Royal Meteorological …, 2008
Mandat: Austrian Science Fund
Interpretable deep learning for spatial analysis of severe hailstorms
DJ Gagne II, SE Haupt, DW Nychka, G Thompson
Monthly Weather Review 147 (8), 2827-2845, 2019
Mandat: US National Science Foundation
30 Years of space–time covariance functions
E Porcu, R Furrer, D Nychka
Wiley Interdisciplinary Reviews: Computational Statistics 13 (2), e1512, 2021
Mandat: Swiss National Science Foundation
A new ensemble-based consistency test for the Community Earth System Model (pyCECT v1. 0)
AH Baker, DM Hammerling, MN Levy, H Xu, JM Dennis, BE Eaton, ...
Geoscientific Model Development 8 (9), 2829-2840, 2015
Mandat: US Department of Energy
Modeling and emulation of nonstationary Gaussian fields
D Nychka, D Hammerling, M Krock, A Wiens
Spatial statistics 28, 21-38, 2018
Mandat: US National Science Foundation
A Bayesian model for quantifying the change in mortality associated with future ozone exposures under climate change
DN Stacey E Alexeeff, Gabriele G Pfister
Biometrics 72 (1), 281-288, 2016
Mandat: US National Science Foundation, US Department of Energy, US National …
Modeling spatial data using local likelihood estimation and a Matérn to spatial autoregressive translation
A Wiens, D Nychka, W Kleiber
Environmetrics 31 (6), e2652, 2020
Mandat: US National Science Foundation
Estimating precipitation extremes using the log‐histospline
WK Huang, DW Nychka, H Zhang
Environmetrics 30 (4), e2543, 2019
Mandat: US National Science Foundation
Data-optimized coronal field model. I. Proof of Concept
K Dalmasse, A Savcheva, SE Gibson, Y Fan, DW Nychka, N Flyer, ...
The Astrophysical Journal 877 (2), 111, 2019
Mandat: US National Science Foundation, US Department of Defense
Parallel cross-validation: A scalable fitting method for Gaussian process models
F Gerber, DW Nychka
Computational Statistics & Data Analysis 155, 107113, 2021
Mandat: US National Science Foundation, Swiss National Science Foundation
Nonstationary positive definite tapering on the plane
E Anderes, R Huser, D Nychka, M Coram
Journal of Computational and Graphical Statistics 22 (4), 848-865, 2013
Mandat: Swiss National Science Foundation
ROAM: A radial-basis-function optimization approximation method for diagnosing the three-dimensional coronal magnetic field
K Dalmasse, DW Nychka, SE Gibson, Y Fan, N Flyer
Frontiers in Astronomy and Space Sciences 3, 24, 2016
Mandat: US National Science Foundation
A model for large multivariate spatial data sets
W Kleiber, D Nychka, S Bandyopadhyay
Statistica Sinica 29 (3), 1085-1104, 2019
Mandat: US National Science Foundation
Regridding uncertainty for statistical downscaling of solar radiation
MD Bailey, D Nychka, M Sengupta, A Habte, Y Xie, S Bandyopadhyay
Advances in Statistical Climatology, Meteorology and Oceanography 9 (2), 103-120, 2023
Mandat: US Department of Energy
Functional forecasting of dissolved oxygen in high‐frequency vertical lake profiles
L Durell, JT Scott, D Nychka, AS Hering
Environmetrics 34 (4), e2765, 2023
Mandat: US National Science Foundation
A Gaussian process model for insulin secretion reconstruction with uncertainty quantification: applications in cystic fibrosis
J Garrish, C Chan, D Nychka, C Diniz Behn
SIAM Journal on Applied Mathematics 84 (3), S65-S81, 2023
Mandat: US National Science Foundation, US National Institutes of Health
Adapting conditional simulation using circulant embedding for irregularly spaced spatial data
MD Bailey, S Bandyopadhyay, D Nychka
Stat 11 (1), e446, 2022
Mandat: US National Science Foundation
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