General description

Advanced course in matrix algebra.

Learning outcomes

The course familiarises students more profoundly with matrix algebra needed when using statistical methods.

Contents

Special attention is paid to projectors, column space, quadratic forms and generalised inverse matrices.

Teaching language

Finnish

Evaluation

Numeric 1-5.

Recommended year of study

1. year autumn
1. year spring
2. year autumn
2. year spring

Study materials

1. Abadir, K. M., Magnus, J. R., Matrix algebra. Cambridge University Press, 2005.
2. Ben-Israel, A., Greville, T. N. E., Generalized inverses: theory and applications, 2nd ed. Springer 2003.
3. Gentle, J. E., Matrix algebra: theory, computations, and applications in statistics. Springer, 2007.
4. Graybill, F. A., Matrices with applications in statistics, 2nd ed. Wadsworth, Belmont 1983.
5. Harville, D. A., Matrix algebra from a statistician’s perspective. Springer, New York 1997.
6. Isotalo, J., Puntanen, S., Styan, G. P. H., Formulas useful for linear regression analysis and related matrix theory, 4th ed. A384/MTL, Tampereen yliopisto 2008.
7. Meyer, C. D., Matrix analysis and applied linear algebra. SIAM 2000.
8. Puntanen, S., Matriiseja tilastotieteilijälle. B47/MTF, University of Tampere 1998.
9. Puntanen, S., Regressioanalyysi I-II. B48-49/MTF, University of Tampere 1999.
10. Puntanen, S., Styan, G. P. H., Isotalo, J., Matrix tricks for linear statistical models: our personal top twenty. Springer, to be published in autumn 2010.
11. Rao, A. R., Bhimasankaram, P., Linear algebra, 2nd ed. Hindustan Book Agency 2000.
12. Rao, C. R., Mitra, S. K., Generalized inverse of matrices and its applications. Wiley 1971.
13. Rao, C. R., Rao, M. B., Matrix algebra and its applications to statistics and econometrics. World Scientific, Singapore 1998.
14. Schott, J. R., Matrix analysis for statistics, 2nd ed. Wiley, New York 2005.
15. Seber, G. A. F., A Matrix handbook for statisticians. Wiley 2007.

Belongs to following study modules