References
- Adler, D., and Murdoch, D. (2011), rgl: 3D Visualization Device System (OpenGL), R package version 0.92.798, Vienna Austria: R Foundation for Statistical Computing.
- Efron, B., Hastie, T., Johnstone, I., and Tibshirani, R. (2004), “Least Angle Regression,” The Annals of Statistics, 32, 407–499.
- Friendly, M., and Kwan, E. (2009), “Where’s Waldo: Visualizing Collinearity Diagnostics,” The American Statistician, 63, 56–65.
- Friendly, M., Monette, G., and Fox, J. (2011), “Elliptical Insights: Understanding Statistical Methods Through Elliptical Geometry,” Statistical Science. Available at http://datavis.ca/papers/ellipses.pdf
- Gabriel, K.R. (1971), “The Biplot Graphic Display of Matrices With Application to Principal Components Analysis,” Biometrics, 58, 453–467.
- Gibbons, D.G. (1981), “A Simulation Study of Some Ridge Estimators,” Journal of the American Statistical Association, 76, 131–139.
- Hall, P. (1987), “On the Bootstrap and Likelihood-Based Confidence Regions,” Biometrika, 74, 481–493.
- ——— (1997), The Bootstrap and Edgeworth Expansion, Berlin: Springer-Verlag, corr. 2nd printing. edn.
- Hastie, T., Tibshirani, R., and Friedman, J.H. (2001), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, New York: Springer-Verlag.
- Hoerl, A.E., and Kennard, R.W. (1970a), “Ridge Regression: Biased Estimation for Nonorthogonal Problems,” Technometrics, 12, 55–67.
- ——— (1970b), “Ridge Regression: Applications to Nonorthogonal Problems,” Technometrics, 12, 69–82, (correction V12, 723).
- Hoerl, A.E., Kennard, R.W., and Baldwin, K.F. (1975), “Ridge Regression: Some Simulations,” Communications in Statistics, 4, 105–123.
- Jensen, D.R., and Ramirez, D.E. (2008), “Anomalies in the Foundations of Ridge Regression,” International Statistical Review, 76, 89–105.
- Lawless, J.F., and Wang, P. (1976), “A Simulation Study of Ridge and Other Regression Estimators,” Communications in Statistics, 5, 307–323.
- Longley, J.W. (1967), “An Appraisal of Least Squares Programs for the Electronic Computer From the Point of View of the User,” Journal of the American Statistical Association, 62, 819–841.
- McDonald, G.C. (2009), “Ridge Regression,” Wiley Interdisciplinary Reviews: Computational Statistics, 1, 93–100.
- R Development Core Team. (2011), R: A Language and Environment for Statistical Computing, Vienna, Austria: R Foundation for Statistical Computing. ISBN 3-900051-07-0.
- Rousseeuw, P., and Leroy, A. (1987), Robust Regression and Outlier Detection, New York: Wiley.
- Rousseeuw, P., and Van Driessen, K. (1999), “A Fast Algorithm for the Minimum Covariance Determinant Estimator,” Technometrics, 41, 212–223.
- Stamey, T., Kabalin, J., McNeal, J., Johnstone, I., Freiha, F., Redwine, E., and Yang, N. (1989), “Prostate Specific Antigen in the Diagnosis and Treatment of Adenocarcinoma of the Prostate: II. Radical Prostatectomy Treated Patients,” Journal of Urology, 141, 1076–1083.
- Tibshirani, R. (1996), “Regression Shrinkage and Selection via the Lasso,” Journal of the Royal Statistical Society, Series B, 58, 267–288.
- Vinod, H.D. (1978), “A Survey of Ridge Regression and Related Techniques for Improvements Over Ordinary Least Squares,” The Review of Economics and Statistics, 60, 121–131.