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Statistics for High-Dimensional Data: Methods, Theory and Applications Peter Bühlmann, Sara van de Geer
Publisher: Springer

Algebra (6-7 lectures) Groups and their representations (except as specified in 5 and 7). High-dimensional data analysis. Van de Geer http://www.eecs.berkeley.edu/~wainwrig/Papers/WaiJor08_FTML.pdf. Series: Springer Series in Statistics. Bühlmann, Peter, van de Geer, Sara. Statistics for High-Dimensional Data: Methods, Theory and Applications By P. These are more than just interesting theoretical developments- they are now implemented in R packages such as SuperLearner and tmle. The process of generating a hypothesis Alan's primarily works on the analysis of high dimensional data using semi-parametric statistical methods in applications such as using prognostic factors in severe trauma patients, the molecular biology of aging, and diarrheal disease in developing countries. The aim of the workshop is to bring together theory and practice in modeling and exploring structure in high-dimensional data. Li's research involves several fields of statistics, including high-dimensional data analysis, variable selection, and intensive longitudinal data analysis. Methods, Theory and Applications. If gesture facilitates learning by eliciting certain eye movements, then this would advance theory and provide educators with a guiding principle for designing learning materials. Random matrices and free probability. Rings, algebras and modules (except . Connections with sections 2, 3, 14, 15. Statistics for High-Dimensional Data.