The purpose of the workshop is to bring together researchers sharing an interest in a variety of aspects of statistics and its applications as well as matrix analysis and its applications to statistics, and offer them a possibility to discuss current developments in these subjects. The workshop will bridge the gap among statisticians, computer scientists and mathematicians in understanding each other's tools. We anticipate that the workshop will stimulate research, in an informal setting, and foster the interaction of researchers in the interface between matrix theory and statistics. Some emphasis will be put on related numerical linear algebra issues and numerical solution methods, relevant to problems arising in statistics. The workshop will include invited talks and a special session with talks and posters by graduate students.
(1) highlight and expand the breadth of existing methods in matrix analysis and their potential for the advance of both mathematical and statistical sciences;
(2) identify important directions for future research in the theory of High dimensional statistical analysis; Linear/multivariate models; Small area estimation (Survey sampling); Applications (signal processing, Bioinformatics); Sufficient dimension reduction; Matrices and computational statistics;
(3) facilitate collaboration between theoretical and subject-area researchers; and
(4) provide opportunities for highly qualified personnel (HQP) to interact with leading international researchers.
The topics that have been selected so far include estimation, prediction and testing in linear models; robustness of relevant statistical methods; estimation of variance components appearing in linear models; generalizations to nonlinear models; design and analysis of experiments, including optimality and comparison of linear experiments; and applications of matrix methods in statistics.