Heteroscedastic kernel ridge regression
โ Scribed by Gavin C. Cawley; Nicola L.C. Talbot; Robert J. Foxall; Stephen R. Dorling; Danilo P. Mandic
- Book ID
- 113813655
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 370 KB
- Volume
- 57
- Category
- Article
- ISSN
- 0925-2312
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
The maximum likelihood estimation in a regression model with heteroscedastic errors is considered. When the design matrices in the model are inappropriately specified, the maximum likelihood estimates of the variances of certain observations are found to be zero irrespective of the observed values,
## 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