Random Field Estimation
Random Field Estimation is a statistical inference method that characterizes the spatial distribution of a stochastic process by predicting the values of a random field at unobserved locations based on observed data and an assumed covariance structure.
187
Publications
8.3K
Citations
345
Authors
229
Institutions
Publications per year
2017–2026
31
Parents
187
Nonstationary cluster-size inference with random field and permutation methods
Satoru Hayasaka, K. Luan Phan, Israel Liberzon et al. · NeuroImage · 2004 · 671 citations
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Centre National de la Recherche Scientifique
Paris, France
10 h-index
17 publications
668 citations
University of California, Davis
Davis, United States
6 h-index
9 publications
218 citations
University of Michigan
Ann Arbor, United States
5 h-index
11 publications
2.5K citations
National University of Singapore
Singapore, Singapore
5 h-index
8 publications
419 citations
Technion – Israel Institute of Technology
Haifa, Israel
4 h-index
4 publications
114 citations
University of California San Diego
San Diego, United States
4 h-index
4 publications
68 citations

City University of Hong Kong
Hong Kong, Hong Kong
4 h-index
5 publications
454 citations

Johns Hopkins University
Baltimore, United States
4 h-index
6 publications
299 citations
1–8 of 229
10 publications · 651 citations
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10 publications · 382 citations
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7 publications · 200 citations
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6 publications · 332 citations
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6 publications · 200 citations
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