Ridge regression (RR) and principal component regression (PCR) are two popular methods intended to overcome the problem of multicollinearity which arises with spectral data. The present study compares the performances of RR and PCR in addition to ordinary least squares (OLS) and partial least square
β¦ LIBER β¦
Which principal components to utilize for principal component regression
β Scribed by Jon M. Sutter; John H. Kalivas; Patrick M. Lang
- Publisher
- John Wiley and Sons
- Year
- 1992
- Tongue
- English
- Weight
- 498 KB
- Volume
- 6
- Category
- Article
- ISSN
- 0886-9383
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