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Titlebook: Chemometrics with R; Multivariate Data An Ron Wehrens Book 2020Latest edition Springer-Verlag GmbH Germany, part of Springer Nature 2020 Mu

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樓主: McKinley
31#
發(fā)表于 2025-3-26 22:20:15 | 只看該作者
Konzeptgebundene Steuerungsverfahren consistent experimental design will be able to prevent this kind of fluctuations. Moreover, biological variation between individuals often dominates measurement variation. The bigger the variation, the more important it is to have enough samples for validation. Only in this way, reliable error esti
32#
發(fā)表于 2025-3-27 04:46:51 | 只看該作者
33#
發(fā)表于 2025-3-27 08:30:43 | 只看該作者
34#
發(fā)表于 2025-3-27 10:03:10 | 只看該作者
Validation able to make accurate predictions (the position of a planet in two weeks’ time) is—in some sense—a “correct” description of reality. In many applications in the natural sciences, unfortunately, validation is hard to do: chemical and biological processes often exhibit quite significant variation unr
35#
發(fā)表于 2025-3-27 13:53:56 | 只看該作者
Chemometric Applicationsiques, found in many textbooks and applicable in a wide range of fields. The topics in this chapter are more specific to the field of chemometrics, combining elements from the previous chapters. In particular, latent-variable approaches like PCA and PLS exhibit a wide range of applications (some peo
36#
發(fā)表于 2025-3-27 20:00:57 | 只看該作者
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發(fā)表于 2025-3-27 23:12:20 | 只看該作者
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發(fā)表于 2025-3-28 02:33:14 | 只看該作者
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發(fā)表于 2025-3-28 08:00:23 | 只看該作者
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發(fā)表于 2025-3-28 14:24:10 | 只看該作者
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