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Geometry of Ridge Regression Illustrated
Benee F. Swindel
The American Statistician
Vol. 35, No. 1 (Feb., 1981), pp. 12-15
Stable URL: http://www.jstor.org/stable/2683577
Page Count: 4
You can always find the topics here!Topics: Least squares, Estimators, Linear regression, Quadrants, Statistical estimation, Estimation bias, Geometry, Collinearity, Regression coefficients, Estimators for the mean
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For tutorial purposes ridge traces are displayed in estimation space for repeated samples from a completely known population. Figures given illustrate the initial advantages accruing to ridge-type shrinkage of the least squares coefficients, especially in some cases of near collinearity. The figures also show that other shrunken estimators may perform better or worse, depending on the parameters and design matrix; and they illustrate the problem of choosing a shrinkage parameter or stopping rule. Thus the figures help motivate results previously established algebraically.
The American Statistician © 1981 American Statistical Association