Local optimization of black-box functions with high or infinite-dimensional inputs: application to nuclear safety-Reference-Cited by-同舟云学术

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Local optimization of black-box functions with high or infinite-dimensional inputs: application to nuclear safety

Published:2017-07-21 Issue:1 Volume:33 Page:467-485
ISSN:0943-4062
Container-title:Computational Statistics
language:en
Short-container-title:Comput Stat

Author:

Roche Angelina^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://link.springer.com/article/10.1007/s00180-017-0751-1/fulltext.html

Reference35 articles.

1. Box GEP, Hunter JS (1957) Multi-factor experimental designs for exploring response surfaces. Ann Math Stat 28(1):195–241

2. Brunel É, Mas A, Roche A (2016) Non-asymptotic adaptive prediction in functional linear models. J Multivariate Anal 143:208–232

3. Cardot H, Ferraty F, Sarda P (1999) Functional linear model. Stat Probab Lett 45(1):11–22

4. Cardot H, Sarda P (2010) Functional linear regression. In: Ferraty F, Romain Y (eds) Handbook of functional data analysis. Oxford University Press, pp 21–46

5. Delaigle A, Hall P (2012) Methodology and theory for partial least squares applied to functional data. Ann Stat 40(1):322–352

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1. Lasso in infinite dimension: application to variable selection in functional multivariate linear regression;Electronic Journal of Statistics;2023-01-01

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