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BRISC: Bootstrap for rapid inference on spatial covariances
Arkajyoti Saha,
Abhirup Datta
Bloomberg School of Public Health
Research output
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Contribution to journal
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Article
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peer-review
2
Scopus citations
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Dive into the research topics of 'BRISC: Bootstrap for rapid inference on spatial covariances'. Together they form a unique fingerprint.
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Business & Economics
Bootstrap
100%
Inference
58%
Bayesian Approach
26%
Resampling
20%
Geostatistics
20%
Parallel Computing
18%
Resampling Methods
18%
Bayesian Model
16%
Gaussian Process
16%
Posterior Distribution
15%
Scalability
14%
Markov Chain Monte Carlo
14%
Parameter Estimation
13%
Decomposition
12%
Sampling
12%
Big Data
11%
Simulation Study
11%
Temperature
11%
Resources
7%
Factors
4%
Mathematics
Bootstrap
65%
Bayesian Approach
23%
Geostatistics
17%
Cholesky Decomposition
16%
Sequential Sampling
15%
Cholesky
15%
Resampling Methods
15%
Subsampling
15%
Parallel Computing
15%
Scalability
15%
Bayesian Model
13%
Resampling
13%
Computational Efficiency
12%
Markov Chain Monte Carlo
12%
Posterior distribution
11%
Gaussian Process
11%
Resources
10%
Parameter Estimation
10%
Simulation Study
8%