This course is organized by the Swedish e-Science Education program (SeSE).

It consists of three parts - self reading/lectures, labs/project preparation. The lectures, if possible, will be given at the Department of Information Technology, Uppsala University. The labs will be organized via Zoom.

Review material for self study (September 7-11, 2020):

• Linear systems, singular/non-singular matrix, (column/row) rank , tridiagonal (band) matrix, LU, and Gaussian elimination.
  Read:
  • (Wikipedia source NLA) or some other introductor text.
• Basic knowledge of stochastic variables, statistical distributions. Read
  • (Wikipedia source Stat) or some other introductor text.
• Those who want to learn R well and use it in the course, should carefully study one of the suggested sources ([1], [2], [3])

Course materials (to be updated during the course)

• Lars Eldén: Lecture 1   Lecture 2     Lecture 3     Lecture 4     Lecture 5     Lab 1   Lab 2     Lab 3  
• Dietrich von Rosen: (Course material to be added)
• Maya Neytcheva: Lecture 1   Lecture 2     Lecture 3     Lecture 4     Lab 1   Lab 2     Files    

Find here nformation on the project work to be done in order to pass the course with full credit

Detailed time schedule (updated)

Date	Topic(s)	Time	Location	Lecturer
September 14	Introduction. General description of the course	9:00-9:15	2345	MN
	Computational Statistics - the statistician's point of view	9:15-11:00	2345	DvR
	Regression analysis, statistical concepts	11:15-12:00	2345	DvR
	Computational Statistics - the numerical analyst's point of view	13:15-14:00	2345	LE
	Regression: Least Squares and QR factorization. Normal equations vs QR factorization	14:15-16:00	2345	LE
	'Hands-on' session: Least Squares and Orthogonal Transformations (Lab 1)		Individual work	LE
September 15	Multivariate regression analysis, sample covariance matrix, higher dimensional problems	9:00-11:00	2345	DvR
	Singular value decomposition	11:15-12:00	2345	MN
	Singular value decomposition and how to compute it, HPC aspects, Applications	13:15-14:00	2345	MN
	'Hands-on' session: SVD	14:15-16:00	Zoom-based	MN
September 16	Discussion of the experience from the last computer lab	9:00-9:15	2345	MN
	Principal Component Analysis (PCA)	9:15-11:00	2345	LE
	'Hands-on' session: PCA	11:15-12:00	Zoom-based	LE
	Networks, graphs, and matrices	13:15-15:00	2345	LE
	'Hands-on' session: networks, graphs, and matrices	15:15-17:00	Zoom-based	LE
September 17	Discussion of the experience from the last computer lab	9:00-9:15	2345	MN
	Sparse matrices - storage formats. Handling sparse matrices in R and MATLAB	9:15-10:00	2345	MN
	Solving least squares problems: direct and iterative methods. Effect of sparse matrices, HPC aspects	10:15-12:00	2345	MN
	'Hands-on' session: sparse and large size matrices; CGLS	13:15-15:00	Zoom-based	MN
September 18	Discussion of the experience from the last computer lab	9:00-9:15	2344	MN
	Pseudo-inverses	9:15-10:00	2344	MN
	Pseudo-inverses. Applications	10:15-12:00	2344	DvR

Recommended books:

1. James E. Gentle, Computational Statistics, Springer, 2009.
2. Lars Eldén. Matrix methods in data mining and pattern recognition, 2nd ed, SIAM, Philadelphia, 2019.
3. Lars Eldén, Linde Wittmeyer-Koch, Hans Bruun-Nielsen, Intrduction to numerical computations, Studentlitteratur, 2001. Freely available here.

1. Peter Dalgaard, Introductory Statistics with R, Springer, 2002.
2. W.John Braun, Duncan J. Murdoch, A First Course in Statistical Programmimg with R, Cambridge University Press, 2007.
3. Geof H. Givens and Jennifer A. Hoeting, Computational Statistics, Wiley, 2005.
4. Wendy L. Martinez and Angel R. Martinez, Computational Statistics Handbook with MATLAB, Chapman & Hall/CRC, 2002.

Organization issues:
Corona-virus related If the situation permits, to enable the participants to fully profit from the our intention is to give the lectures in person. The lab sessions will be organized via Zoom. We will follow the general instructions to have a sufficient distance between us while working. Also, we discourage you to attend the lectures in case you have some symptoms, that could be related to the corona virus effects.
Some instructions how to find us in Uppsala are to be found here .