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
Local influence in ridge regression
β Scribed by Lei Shi; Xueren Wang
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 233 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0167-9473
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