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

3. year autumn

Study materials

1. Ben-Israel, A., Greville, T. N. E., Generalized Inverses: Theory and Applications, 2nd ed. Springer 2003.
2. Isotalo, J., Puntanen, S., Styan, G. P. H., Formulas Useful for Linear Regression Analysis and Related Matrix Theory. A350/MTF, Tampereen yliopisto 2005.
3. Harville, D. A., Matrix Algebra from a Statistician’s Perspective. Springer, New York 1997.
4. Puntanen, S., Matriiseja tilastotieteilijälle. B47/MTF, Tampereen yliopisto 1998.
5. Puntanen, S., Regressioanalyysi I - II. B48-49/MTF, Tampereen yliopisto 1999.
6. Rao, C. R., Mitra, S. K., Generalized Inverse of Matrices and Its applications. Wiley 1971.
7. Isotalo, J., Puntanen, S., Styan, G. P. H., Matrix Tricks for Linear Statistical Models: Our Personal Top Sixteen. A363/MTF, Tampereen yliopisto 2005.
8. Graybill, F. A., Matrices with Applications in Statistics 2nd ed. Wadsworth, Belmont 1983.
9. Schott, J. R., Matrix Analysis for Statistics, 2nd ed., Wiley, New York 2005.
10. Rao, A. R., Bhimasankaram, P., Linear Algebra, 2nd ed. Hindustan Book Agency 2000.
11. Rao, C. R., Rao, M. B., Matrix Algebra and its Applications to Statistics and Econometrics. World Scientific, Singapore 1998.
12. Meyer, C. D., Matrix Analysis and Applied Linear Algebra. SIAM 2000.
13. Seber, G. A. F., A Matrix Handbook for Statisticians. Wiley 2007.
14. Gentle, J. E., Matrix Algebra: Theory, Computations, and Applications in Statistics. Springer, 2007.

Belongs to following study modules