| dc.contributor.author | Martens, Harald | |
| dc.date.accessioned | 2016-02-08T14:45:21Z | |
| dc.date.accessioned | 2016-06-20T13:11:26Z | |
| dc.date.available | 2016-02-08T14:45:21Z | |
| dc.date.available | 2016-06-20T13:11:26Z | |
| dc.date.issued | 2015 | |
| dc.identifier.citation | Journal of Chemometrics 2015, 29(11):563-581 | nb_NO |
| dc.identifier.issn | 0886-9383 | |
| dc.identifier.uri | http://hdl.handle.net/11250/2393285 | |
| dc.language.iso | eng | nb_NO |
| dc.publisher | John Wiley & Sons Ltd. | nb_NO |
| dc.title | Quantitative Big Data: where chemometrics can contribute | nb_NO |
| dc.type | Journal article | nb_NO |
| dc.type | Peer reviewed | nb_NO |
| dc.date.updated | 2016-02-08T14:45:21Z | |
| dc.rights.holder | © 2015 The Authors Journal of Chemometrics Published by John Wiley & Sons Ltd. | nb_NO |
| dc.source.pagenumber | 563-581 | nb_NO |
| dc.source.volume | 29 | nb_NO |
| dc.source.journal | Journal of Chemometrics | nb_NO |
| dc.source.issue | 11 | nb_NO |
| dc.identifier.doi | 10.1002/cem.2740 | |
| dc.identifier.cristin | 1316067 | |
| dc.description.localcode | This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made | nb_NO |
