An explanation of the use of principal-components analysis to detect and correct for multicollinearity
- 1 September 1992
- journal article
- Published by Elsevier in Preventive Veterinary Medicine
- Vol. 13 (4) , 261-275
- https://doi.org/10.1016/0167-5877(92)90041-d
Abstract
No abstract availableThis publication has 14 references indexed in Scilit:
- The Use of Regression for Detecting Competition with Multicollinear DataEcology, 1988
- A Review of Multivariate AnalysisStatistical Science, 1987
- Selecting principal components in regressionStatistics & Probability Letters, 1985
- A Critique of Some Ridge Regression MethodsJournal of the American Statistical Association, 1980
- Multicollinearity and the value of a priori informationCommunications in Statistics - Theory and Methods, 1979
- Biased Estimation in Regression: An Evaluation Using Mean Squared ErrorJournal of the American Statistical Association, 1977
- Regression analysis and problems of multicollinearityCommunications in Statistics, 1975
- On the Investigation of Alternative Regressions by Principal Component AnalysisJournal of the Royal Statistical Society Series C: Applied Statistics, 1973
- Principal Components Regression in Exploratory Statistical ResearchJournal of the American Statistical Association, 1965
- Analysis of a complex of statistical variables into principal components.Journal of Educational Psychology, 1933