American Society for Quality Ridge Regression : Biased Estimation for Nonorthogonal Problems

  title={American Society for Quality Ridge Regression : Biased Estimation for Nonorthogonal Problems},
  author={Arthur E. Hoerl and Robert W. Kennard},
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. 

From This Paper

Figures, tables, and topics from this paper.

Explore Further: Topics Discussed in This Paper


Publications referenced by this paper.
Showing 1-10 of 21 references

The Logic of Least Squares,

  • G A.
  • 1963
Highly Influential
3 Excerpts

Selection of the Best Subset

  • R. R. Hocking, R. N. Leslie
  • 1967
2 Excerpts

Factor Analysis and Regression

  • J. T. Scott
  • 1966
2 Excerpts

Selection of Variables for Fitting Equations to Data," Technometrics

  • J. W. Gorman, R. J. Toman
  • 1966
2 Excerpts

The Best Subset in Multiple Regression Analysis,

  • M. J. Garside
  • Applied Statistics,
  • 1965
2 Excerpts

Using the Observations to Estimate Prior Distribution,

  • 1965

An Operator Theoretic Formulation of a Class of Control Problems and a Steepest Descent Method of Solution

  • A. V. Balakrishnan
  • 1963

Application of Ridge Analysis to Regression Problems,

  • A. E. Hoerl
  • Chemical Engineering Progress,
  • 1962
1 Excerpt

Applied Statistical Decision Theory, Boston

  • H. Raiffa, R. Schlaifer
  • 1961
2 Excerpts

Multiple Regression Analysis," in Mathematical Methodsfor

  • M. A. Efroymson
  • Digital Computers,
  • 1960