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Practical Use of Ridge Regression: A Challenge Met
Arthur E. Hoerl, Robert W. Kennard and Roger W. Hoerl
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 34, No. 2 (1985), pp. 114-120
Stable URL: http://www.jstor.org/stable/2347363
Page Count: 7
You can always find the topics here!Topics: Modeling, Correlations, Least squares, Statistical models, Spectral reflectance, Mathematical vectors, Row transformations, Correlation coefficients, Standard deviation, Linear regression
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Fearn (1983) presented regression data and an assessment of the data and regression analysis techniques which we assert to be incorrect. First, the conclusion that the relevant information is associated with the small eigenvalues of the explanatory variables correlation matrix is disputed. Secondly, there was a failure to rectify the effect of the artificial correlations introduced by the reflectance spectroscopy. The removal of these correlations makes it possible to obtain a near-orthogonal system with better predicting power, using ridge regression.
Journal of the Royal Statistical Society. Series C (Applied Statistics) © 1985 Royal Statistical Society