Large datasets, bias and model‐oriented optimal design of experiments-Reference-Cited by-同舟云学术

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Large datasets, bias and model‐oriented optimal design of experiments

Published:2022-07-07 Issue:2 Volume:39 Page:532-545
ISSN:0748-8017
Container-title:Quality and Reliability Engineering International
language:en
Short-container-title:Quality & Reliability Eng

Author:

Pesce Elena¹,Porro Francesco²,Riccomagno Eva²^ORCID

Affiliation:

1. Swiss Re Institute Zurich Switzerland

2. Department of Mathematics University of Genova Genova Italy

Publisher

Wiley

Subject

Management Science and Operations Research,Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qre.3165

Reference22 articles.

1. DeldossiL TommasiC.Big Data and model‐based survey sampling.arXiv preprint arXiv:2002.04255.2020.

2. Statistics in the big data era: Failures of the machine

3. When small data beats big data

4. FlassigRJ SchenkendorfR.Model‐based design of experiments: where to go?9th Vienna Conference on Mathematical Modelling MATHMOD 2018 Extended Abstract Volume Vienna Austria.2018:21‐23.

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1. The ENBIS‐21 quality and reliability engineering international special issue;Quality and Reliability Engineering International;2023-01-24

2. Generation of all randomizations using circuits;Annals of the Institute of Statistical Mathematics;2022-12-23

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