کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1137464 | 1489172 | 2010 | 11 صفحه PDF | دانلود رایگان |
With a simple transformation, the ordinary least squares objective can yield a family of modified ridge regressions which outperforms the regular ridge model. These models have more stable coefficients and a higher quality of fit with the growing profile parameter. With an additional adjustment based on minimization of the residual variance, all the characteristics become even better: the coefficients of these regressions do not shrink to zero when the ridge parameter increases, the coefficient of multiple determination stays high, while bias and generalized cross-validation are low. In contrast to regular ridge regression, the modified ridge models yield robust solutions with various values of the ridge parameter, encompass interpretable coefficients, and good quality characteristics.
Journal: Mathematical and Computer Modelling - Volume 51, Issues 5–6, March 2010, Pages 338–348