## Abstract Ridge regression is a popular parameter estimation method used to address the collinearity problem frequently arising in multiple linear regression. The formulation of the ridge methodology is reviewed and properties of the ridge estimates capsulated. In particular, four rationales lead
Ridge regression revisited
β Scribed by Paul M. C. de Boer; Christian M. Hafner
- Book ID
- 111014276
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 163 KB
- Volume
- 59
- Category
- Article
- ISSN
- 0039-0402
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
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
## Abstract Ridge regression is a parameter estimation method used to address the collinearity problem frequently arising in multiple linear regressions. The methodology defines a class of estimators indexed by a nonβnegative scalar parameter, __k__. When utilizing ridge regression, the analyst eve