Chemometrics Calculations with Microsoft Excel (4) - Principal Component Regression -
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- YOSHIMURA Norio
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology
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- FUKUHARA Koji
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology
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- MITSUKI Kenichiro
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology
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- TAKAYANAGI Masao
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology
Bibliographic Information
- Other Title
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- Microsoft Excelを用いたケモメトリクス計算(4) -主成分回帰-
- Microsoft Excel オ モチイタ ケモメトリクス ケイサン(4)シュセイブン カイキ
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Description
Although chemometrics has become widely used recently for analyzing experimental chemical data, there exist only a few instructions for the proper usage of chemometrics other than those in some introductory books. As the fourth step of chemometrics calculations with Microsoft Excel (Excel), the principal component regression is performed on worksheets. Three worksheets were constructed for generating the spectra of model calibration samples and unknown samples, solving principal component analysis by NIPALS algorithm and calculating principal component regression. The quantitative performance of principal component regression was compared with that of multiple linear regression or the analysis based on Lambert-Beer law. Principal component regression was found to be superior to the other two methods.
Journal
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- Journal of Computer Chemistry, Japan
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Journal of Computer Chemistry, Japan 10 (1), 32-43, 2011
Society of Computer Chemistry, Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001205178125696
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- NII Article ID
- 10031135584
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- NII Book ID
- AA11657986
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- COI
- 1:CAS:528:DC%2BC38XivF2mt70%3D
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- ISSN
- 13473824
- 13471767
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- NDL BIB ID
- 023533243
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL Search
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed