This course is organized by the Swedish eScience Education program (SeSE).
It consists of three parts  self reading, lectures and labs, and project preparation. The lectures and the labs will be given at the Department Information Technology, Uppsala University.
Date  Topic(s)  Time  Location 
Lecturer 

Sep 22  Introduction. General description of the course  9:159:30  2414b 
MN 
Computational Statistics  the statistician's point of view  9:3011:00  2414b 
DvR 

Computational Statistics  the numerical analyst's point of view  11:1512:00  2414b 
LE 

Least Squares and QR factorization. Normal equations vs QR factorization.  13:1515:00  2414b 
LE 

Regression analysis, statistical concepts  15:1516:00  2414b 
DvR 

Sep 23  Singular value decomposition (SVD). Pseudoinverses. Applications  9:1512:00  2414b 
MN 
Computer lab and 'Handson' session: QR, illconditioning, SVD, large scale problems  13:1517:00  2315 
MN 

Sep 24  Discussion of the experience from the last computer lab  9:159:30  2414b 
MN 
Principal Component Analysis (PCA)  9:3012:00  2414b 
DvR 

Computer lab and 'Handson' session: ...  13:1517:00  2315 
DvR MN 

Sep 25  Discussion of the experience from the last computer lab  9:159:30  2414b 
MN 
Partial Least Squares (PLS)  9:3012:00  2414b 
LE 

Computer lab and 'Handson' session: PCA, PLS  13:1517:00  1312 
LE 

Sep 26  Discussion of the experience from the last computer lab  9:159:30  2414b 
MN 
Regression problems leading to sparse matrices. Sparse matrices  storage formats. Solving least squares problems with sparse matrices: direct and iterative methods. Computing the SVD  9:3012:00  2414b 
MN 

Handling sparse matrices in R and MATLAB. Briefly on Parallel Statistical computing. Summary of the course material.  13:1515:00  2414b 
MN 
Recommended books:
Organization issues:
Some instructions how to find us in Uppsala are to be found here .
Suggested hotel to book rooms in Uppsala:
Hotel Uppsala .