𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Ridge regression

✍ Scribed by Gary C. McDonald


Publisher
Wiley (John Wiley & Sons)
Year
2009
Tongue
English
Weight
135 KB
Volume
1
Category
Article
ISSN
0163-1829

No coin nor oath required. For personal study only.

✦ Synopsis


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 leading to a regression estimator of the ridge form are summarized. Algebraic properties of the ridge regression coefficients are given, which elucidate the behavior of a ridge trace for small values of the ridge parameter (i.e., close to the least squares solution) and for large values of the ridge parameter. Further properties involving coefficient sign changes and rates‐of‐change, as functions of the ridge parameter, are given for specific correlation structures among the independent variables. These results help relate the visual behavior of a ridge trace to the underlying structure of the data. Copyright Β© 2009 John Wiley & Sons, Inc.

This article is categorized under:

Statistical Models > Linear Models

Algorithms and Computational Methods > Least Squares


πŸ“œ SIMILAR VOLUMES


Principal component regression, ridge re
✍ E. Vigneau; M. F. Devaux; E. M. Qannari; P. Robert πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 160 KB πŸ‘ 2 views

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

Tracing ridge regression coefficients
✍ Gary C. McDonald πŸ“‚ Article πŸ“… 2010 πŸ› Wiley (John Wiley & Sons) 🌐 English βš– 145 KB

## 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 non‐negative scalar parameter, __k__. When utilizing ridge regression, the analyst eve

A note on ridge regression
✍ J.S. Chawla πŸ“‚ Article πŸ“… 1990 πŸ› Elsevier Science 🌐 English βš– 141 KB
Local influence in ridge regression
✍ Lei Shi; Xueren Wang πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 233 KB
Ridge regression in two-parameter soluti
✍ Stan Lipovetsky; W. Michael Conklin πŸ“‚ Article πŸ“… 2005 πŸ› John Wiley and Sons 🌐 English βš– 140 KB πŸ‘ 2 views