A1 Journal article (refereed)
Efficient spatial designs using Hausdorff distances and Bayesian optimization (2022)


Paglia, J., Eidsvik, J., & Karvanen, J. (2022). Efficient spatial designs using Hausdorff distances and Bayesian optimization. Scandinavian Journal of Statistics, 49(3), 1060-1084. https://doi.org/10.1111/sjos.12554


JYU authors or editors


Publication details

All authors or editorsPaglia, Jacopo; Eidsvik, Jo; Karvanen, Juha

Journal or seriesScandinavian Journal of Statistics

ISSN0303-6898

eISSN1467-9469

Publication year2022

Publication date20/09/2021

Volume49

Issue number3

Pages range1060-1084

PublisherWiley-Blackwell

Publication countryUnited Kingdom

Publication languageEnglish

DOIhttps://doi.org/10.1111/sjos.12554

Publication open accessOpenly available

Publication channel open accessPartially open access channel

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/78515


Abstract

An iterative Bayesian optimisation technique is presented to find spatial designs of data that carry much information. We use the decision theoretic notion of value of information as the design criterion. Gaussian process surrogate models enable fast calculations of expected improvement for a large number of designs, while the full-scale value of information evaluations are only done for the most promising designs. The Hausdorff distance is used to model the similarity between designs in the surrogate Gaussian process covariance representation, and this allows the suggested algorithm to learn across different designs. We study properties of the Bayesian optimisation design algorithm in a synthetic example and real-world examples from forest conservation and petroleum drilling operations. In the synthetic example we consider a model where the exact solution is available and we run the algorithm under different versions of this example and compare it with existing approaches such as sequential selection and an exchange algorithm.


Keywordsspatial analysisdecision support systemsoptimisationBayesian analysis

Free keywordsBayesian optimisation; Hausdorff distance; value of information


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Ministry reportingYes

Reporting Year2022

JUFO rating2


Last updated on 2024-30-04 at 17:36