Overview of Low-rank and Sparse Techniques in Spatial Statistics and Parameter Identification

Abstract
Motivation: improve statistical model by implementing more efficient numerical tools
Major Goal: Develop new statistical tools to address new problems.
Overview: Low-rank matrices, Sparse matrices, Hierarchical matrices.
Approximation of Matern covariance functions and joint Gaussian likelihood,
Identification of unknown parameters via maximizing Gaussian log-likelihood,
Low-rank tensor methods

Description
Talk given on KAUST Biostatistics Group Seminar

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