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Computational improvements to estimating Kriging metamodel parameters
Jay D. Martin
Applied Research Laboratory (ARL)
Research output
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Contribution to journal
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Article
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peer-review
51
Scopus citations
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Keyphrases
Kriging Model
100%
Response Surface
50%
Computational Burden
33%
Linear Regression
16%
Gradient Method
16%
Computationally Efficient
16%
Computationally Expensive
16%
Surface Mounting
16%
Likelihood Function
16%
Maximum Likelihood Estimation
16%
Hessian
16%
Trade Space
16%
Log-likelihood Ratio
16%
Implementation Details
16%
Spatial Correlation
16%
Original Model
16%
System Design Analysis
16%
Surrogate Model
16%
Complex Response
16%
Potential Reduction
16%
Engineering
Kriging Model
100%
Model Parameter
50%
Response Surface
50%
Spatial Correlation
33%
Gaussians
16%
Design Analysis
16%
Surrogate Model
16%
Maximum Likelihood Estimation
16%
Mathematics
Kriging
100%
Response Surface
42%
Spatial Correlation
28%
Concludes
14%
Statistics
14%
Optimal Model
14%
Gaussian Distribution
14%
Linear Regression
14%
Maximum Likelihood Estimation
14%
Gradient-Based Method
14%
Likelihood Equation
14%
Biochemistry, Genetics and Molecular Biology
Surface Property
100%
Gaussian Distribution
33%
Earth and Planetary Sciences
Kriging
100%
Design Analysis
14%