Noisy kriging-based optimization methods: a unified implementation within the DiceOptim package
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Publication:1621383
DOI10.1016/j.csda.2013.03.018zbMath1471.62161OpenAlexW2023668266MaRDI QIDQ1621383
David Ginsbourger, Victor Picheny
Publication date: 8 November 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://boris.unibe.ch/41533/8/Noisy%20kriging-based%20optimization%20methods%20a%20unified%20implementation%20within%20the%20DiceOptim%20package.pdf
Computational methods for problems pertaining to statistics (62-08) Software, source code, etc. for problems pertaining to statistics (62-04)
Related Items (6)
Special issue on statistical algorithms and software in R ⋮ Conditional optimization of a noisy function using a kriging metamodel ⋮ TREGO: a trust-region framework for efficient global optimization ⋮ Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise ⋮ DiceOptim ⋮ Analyzing stochastic computer models: a review with opportunities
Uses Software
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