Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics

Sagnik Mondal; Sameh Abdulah; Hatem Ltaief; Ying Sun; Marc G. Genton; David E. Keyes

Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics

Sagnik Mondal, Sameh Abdulah, Hatem Ltaief, Ying Sun, Marc G. Genton, David E. Keyes

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English (US)
Title of host publication	Accepted in "International Parallel and Distributed Processing Symposium, 2022"
Publisher	IEEE
State	Published - 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-02-19
Acknowledgements: This work is funded and supported by King Abdullah University of Science and Technology (KAUST) through the Office of Sponsored Research (OSR). We would also like to acknowledge Intel for support in the form of an Intel Parallel Computing Center award Cray for the support provided during the Center of Excellence award to the Extreme Computing Research Center at KAUST. This research used the resources of the Extreme Computing Research Center (ECRC) and the KAUST Supercomputing Laboratory, including Cray XC40, Shaheen II supercomputer.

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@inproceedings{64d531cc25a24a28afbb8ca2b285ba07,

title = "Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics",

author = "Sagnik Mondal and Sameh Abdulah and Hatem Ltaief and Ying Sun and Genton, {Marc G.} and Keyes, {David E.}",

note = "KAUST Repository Item: Exported on 2022-02-19 Acknowledgements: This work is funded and supported by King Abdullah University of Science and Technology (KAUST) through the Office of Sponsored Research (OSR). We would also like to acknowledge Intel for support in the form of an Intel Parallel Computing Center award Cray for the support provided during the Center of Excellence award to the Extreme Computing Research Center at KAUST. This research used the resources of the Extreme Computing Research Center (ECRC) and the KAUST Supercomputing Laboratory, including Cray XC40, Shaheen II supercomputer.",

year = "2022",

language = "English (US)",

booktitle = "Accepted in {"}International Parallel and Distributed Processing Symposium, 2022{"}",

publisher = "IEEE",

}

TY - GEN

T1 - Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics

AU - Mondal, Sagnik

AU - Abdulah, Sameh

AU - Ltaief, Hatem

AU - Sun, Ying

AU - Genton, Marc G.

AU - Keyes, David E.

N1 - KAUST Repository Item: Exported on 2022-02-19 Acknowledgements: This work is funded and supported by King Abdullah University of Science and Technology (KAUST) through the Office of Sponsored Research (OSR). We would also like to acknowledge Intel for support in the form of an Intel Parallel Computing Center award Cray for the support provided during the Center of Excellence award to the Extreme Computing Research Center at KAUST. This research used the resources of the Extreme Computing Research Center (ECRC) and the KAUST Supercomputing Laboratory, including Cray XC40, Shaheen II supercomputer.

PY - 2022

Y1 - 2022

UR - http://hdl.handle.net/10754/675552

M3 - Conference contribution

BT - Accepted in "International Parallel and Distributed Processing Symposium, 2022"

PB - IEEE

ER -

Parallel Approximations of the Tukey g-and-h Likelihoods and Predictions for Non-Gaussian Geostatistics

Bibliographical note

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