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Gaussian Process Emulators for Computer Experiments with Inequality Constraints

Physical phenomena are observed in many fields (science and engineering) and are often studied by time-consuming computer codes. These codes are analyzed with statistical models, often called emulators. In many situations, the physical system (computer model output) may be known to satisfy inequalit... Full description

Journal Title: Mathematical geosciences 2017, Vol.49 (5), p.557-582
Main Author: Maatouk, Hassan
Other Authors: Bay, Xavier
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: Berlin/Heidelberg: Springer Berlin Heidelberg
ID: ISSN: 1874-8961
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recordid: cdi_gale_infotracmisc_A494760795
title: Gaussian Process Emulators for Computer Experiments with Inequality Constraints
format: Article
creator:
  • Maatouk, Hassan
  • Bay, Xavier
subjects:
  • Analysis
  • Article
  • Chemistry and Earth Sciences
  • Computer Science
  • Earth and Environmental Science
  • Earth Sciences
  • Equality
  • Gaussian processes
  • general
  • Geotechnical Engineering & Applied Earth Sciences
  • Hydrogeology
  • Physics
  • Statistics for Engineering
ispartof: Mathematical geosciences, 2017, Vol.49 (5), p.557-582
description: Physical phenomena are observed in many fields (science and engineering) and are often studied by time-consuming computer codes. These codes are analyzed with statistical models, often called emulators. In many situations, the physical system (computer model output) may be known to satisfy inequality constraints with respect to some or all input variables. The aim is to build a model capable of incorporating both data interpolation and inequality constraints into a Gaussian process emulator. By using a functional decomposition, a finite-dimensional approximation of Gaussian processes such that all conditional simulations satisfy the inequality constraints in the entire domain is proposed. To show the performance of the proposed model, some conditional simulations with inequality constraints such as boundedness, monotonicity or convexity conditions in one and two dimensions are given. A simulation study to investigate the efficiency of the method in terms of prediction is included.
language: eng
source:
identifier: ISSN: 1874-8961
fulltext: no_fulltext
issn:
  • 1874-8961
  • 1874-8953
url: Link


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descriptionPhysical phenomena are observed in many fields (science and engineering) and are often studied by time-consuming computer codes. These codes are analyzed with statistical models, often called emulators. In many situations, the physical system (computer model output) may be known to satisfy inequality constraints with respect to some or all input variables. The aim is to build a model capable of incorporating both data interpolation and inequality constraints into a Gaussian process emulator. By using a functional decomposition, a finite-dimensional approximation of Gaussian processes such that all conditional simulations satisfy the inequality constraints in the entire domain is proposed. To show the performance of the proposed model, some conditional simulations with inequality constraints such as boundedness, monotonicity or convexity conditions in one and two dimensions are given. A simulation study to investigate the efficiency of the method in terms of prediction is included.
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subjectAnalysis ; Article ; Chemistry and Earth Sciences ; Computer Science ; Earth and Environmental Science ; Earth Sciences ; Equality ; Gaussian processes ; general ; Geotechnical Engineering & Applied Earth Sciences ; Hydrogeology ; Physics ; Statistics for Engineering
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abstractPhysical phenomena are observed in many fields (science and engineering) and are often studied by time-consuming computer codes. These codes are analyzed with statistical models, often called emulators. In many situations, the physical system (computer model output) may be known to satisfy inequality constraints with respect to some or all input variables. The aim is to build a model capable of incorporating both data interpolation and inequality constraints into a Gaussian process emulator. By using a functional decomposition, a finite-dimensional approximation of Gaussian processes such that all conditional simulations satisfy the inequality constraints in the entire domain is proposed. To show the performance of the proposed model, some conditional simulations with inequality constraints such as boundedness, monotonicity or convexity conditions in one and two dimensions are given. A simulation study to investigate the efficiency of the method in terms of prediction is included.
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pubSpringer Berlin Heidelberg
doi10.1007/s11004-017-9673-2
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