Large datasets, bias and model‐oriented optimal design of experiments. (7th July 2022)
- Record Type:
- Journal Article
- Title:
- Large datasets, bias and model‐oriented optimal design of experiments. (7th July 2022)
- Main Title:
- Large datasets, bias and model‐oriented optimal design of experiments
- Authors:
- Pesce, Elena
Porro, Francesco
Riccomagno, Eva - Other Names:
- Bischoff Jens guestEditor.
Lepore Antonio guestEditor. - Abstract:
- Abstract: We review recent literature that proposes to adapt ideas from classical model based optimal design of experiments to problems of data selection of large datasets. Special attention is given to bias reduction and to protection against confounders. Some new results are presented. Theoretical and computational comparisons are made.
- Is Part Of:
- Quality and reliability engineering international. Volume 39:Number 2(2023)
- Journal:
- Quality and reliability engineering international
- Issue:
- Volume 39:Number 2(2023)
- Issue Display:
- Volume 39, Issue 2 (2023)
- Year:
- 2023
- Volume:
- 39
- Issue:
- 2
- Issue Sort Value:
- 2023-0039-0002-0000
- Page Start:
- 532
- Page End:
- 545
- Publication Date:
- 2022-07-07
- Subjects:
- confounders -- large datasets -- model bias -- optimal experimental design
Reliability (Engineering) -- Periodicals
Quality control -- Periodicals
High technology -- Periodicals
620.00452 - Journal URLs:
- http://www3.interscience.wiley.com/cgi-bin/jhome/3680 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/qre.3165 ↗
- Languages:
- English
- ISSNs:
- 0748-8017
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7168.137300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 25717.xml