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A note on principal component analysis for multi-dimensional data

✍ Scribed by Jianguo Sun

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
77 KB
Volume
46
Category
Article
ISSN
0167-7152

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✦ Synopsis

We consider the application of principal component analysis (PCA) to the analysis of high-dimension data with the analysis goal being calibration. Two commonly used versions of PCA are compared and it is showed that contrast to the expected, the simpliΓΏed version could underestimate prediction error and give misleading results.

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