A note on principal component analysis for multi-dimensional data

Jianguo Sun

Statistics & Probability Letters, 2000, vol. 46, issue 1, 69-73

Abstract: 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 simplified version could underestimate prediction error and give misleading results.

Keywords: Calibration; Prediction; Root; mean; square; error; of; prediction; Validation (search for similar items in EconPapers)
Date: 2000
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