Overview of Low-rank and Sparse Techniques in Spatial Statistics and Parameter Identification
Type
PresentationAuthors
Litvinenko, AlexanderKAUST Department
Bayesian Computational Statistics & Modeling groupComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Statistics Program
Date
2018-10-03Abstract
Motivation: improve statistical model by implementing more efficient numerical toolsMajor 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