Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-26T12:47:34.075Z Has data issue: false hasContentIssue false
  • English
  • Français

Generalized Sverdrup's Lemma and the Treatment of Less than Full Rank Regression Model

Published online by Cambridge University Press:  20 November 2018

D. G. Kabe
D. G. Kabe*
Affiliation:
Saint Mary's University and, Dalhousie University, Halifax, Nova Scotia, Canada
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Generalized Sverdrup's lemma, Kabe [5], is used here to give a more direct treatment of less than full rank regression model.

Type
Research Article
Information
Canadian Mathematical Bulletin , Volume 17 , Issue 3 , 01 September 1974 , pp. 417 - 419
Copyright
Copyright © Canadian Mathematical Society 1974

References

1. Anderson, T. W., An introduction to multivariate Statistical Analysis, John Wiley, New York (1958).Google Scholar
2. Chakrabarti, M. C., Mathematics of Design and Analysis of Experiments. Asia publishing house, Bombay (1962).Google Scholar
3. Gray bill, F. A., An Introduction to linear statistical Models Vol. 1, McGraw-Hill, New York (1961).Google Scholar
4. John, Peter W. M., Pseudo inverse in the analysis of variance, Ann. Math. Statist. 35 (1964), 895-96.Google Scholar
5. Kabe, D. G., Generalization of Sverdrup′s lemma and its applications to multivariate distribution theory, Ann. Math. Statist. 36 (1965), 671-676.Google Scholar
6. Kabe, D. G., Multivariate linear hypothesis with linear restrictions, J. Roy. Statist. Ass. B 25 (1963), 348-351.Google Scholar
7. Odell, P. L. and Lewis, T. O, A Generalization of Gauss-Markov theorem, J. Ameri. Stat. Ass. 61 (1966), 1063-1066.Google Scholar
8. Plackett, R. L., Some theorems in least squares, Biometrika 37 (1950), 149-157.Google Scholar
9. Rao, C. R., Linear Statistical Inference and Its Applications. John Wiley, New York (1965).Google Scholar