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Collaborations and top research areas from the last five years
Research output
- 20 Article
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On local maxima of smooth Gaussian nonstationary processes and stationary planar fields with trends
Cheng, D., Mar 2025, In: Stochastic Processes and their Applications. 181, 104560.Research output: Contribution to journal › Article › peer-review
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An approximation to peak detection power using Gaussian random field theory
Zhao, Y., Cheng, D. & Schwartzman, A., Nov 2024, In: Journal of Multivariate Analysis. 204, 105346.Research output: Contribution to journal › Article › peer-review
Open Access1 Link opens in a new tab Scopus citations -
Micro-DeMix: a mixture beta-multinomial model for investigating the heterogeneity of the stool microbiome compositions
Liu, R., Wang, Y. & Cheng, D., Dec 1 2024, In: Bioinformatics. 40, 12, btae667.Research output: Contribution to journal › Article › peer-review
Open Access -
Network Inference Using the Hub Model and Variants
He, Z., Zhao, Y., Bickel, P., Weko, C., Cheng, D. & Wang, J., 2024, In: Journal of the American Statistical Association. 119, 546, p. 1264-1273 10 p.Research output: Contribution to journal › Article › peer-review
1 Link opens in a new tab Scopus citations -
Smooth Matérn Gaussian random fields: Euler characteristic, expected number and height distribution of critical points
Cheng, D., Jul 2024, In: Statistics and Probability Letters. 210, 110116.Research output: Contribution to journal › Article › peer-review
1 Link opens in a new tab Scopus citations
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Collaborative Research: A Geostatistical Framework for Spatiotemporal Extremes
Cheng, D. (PI)
National Science Foundation (NSF)
7/1/23 → 6/30/26
Project: Research project
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Extremes of random fields: critical points, excursion components and their statistical applications
Cheng, D. (PI)
9/1/21 → 8/31/26
Project: Research project
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Spatial inference methods for image analysis
Cheng, D. (PI)
HHS: National Institutes of Health (NIH)
8/13/19 → 1/31/23
Project: Research project
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Collaborative Research: Critical Points and Excursion Probability...
Cheng, D. (PI)
National Science Foundation (NSF)
9/10/18 → 6/30/22
Project: Research project
Datasets
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Network Inference Using the Hub Model and Variants
He, Z. (Creator), Zhao, Y. (Creator), Bickel, P. (Creator), Weko, C. (Creator), Cheng, D. (Creator) & Wang, J. (Creator), Taylor & Francis, 2023
DOI: 10.6084/m9.figshare.22141181.v3, https://tandf.figshare.com/articles/dataset/Network_Inference_Using_the_Hub_Model_and_Variants/22141181/3
Dataset
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Network Inference Using the Hub Model and Variants
He, Z. (Creator), Zhao, Y. (Creator), Bickel, P. (Creator), Weko, C. (Creator), Cheng, D. (Creator) & Wang, J. (Creator), Taylor & Francis, 2023
DOI: 10.6084/m9.figshare.22141181, https://tandf.figshare.com/articles/dataset/Network_Inference_Using_the_Hub_Model_and_Variants/22141181
Dataset
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Network Inference Using the Hub Model and Variants
He, Z. (Creator), Zhao, Y. (Creator), Bickel, P. (Creator), Weko, C. (Creator), Cheng, D. (Creator) & Wang, J. (Creator), Taylor & Francis, 2023
DOI: 10.6084/m9.figshare.22141181.v2, https://tandf.figshare.com/articles/dataset/Network_Inference_Using_the_Hub_Model_and_Variants/22141181/2
Dataset
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Network Inference Using the Hub Model and Variants
He, Z. (Creator), Zhao, Y. (Creator), Bickel, P. (Creator), Weko, C. (Creator), Cheng, D. (Creator) & Wang, J. (Creator), Taylor & Francis, 2023
DOI: 10.6084/m9.figshare.22141181.v1, https://tandf.figshare.com/articles/dataset/Network_Inference_Using_the_Hub_Model_and_Variants/22141181/1
Dataset