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Document type:
Masterarbeit 
Author(s):
Matthieu Bulté 
Title:
Higher-order statistics for high-dimensional problems with applications to graphical models 
Abstract:
A Gaussian graphical model is a statistical model, where the data follows a multivariate Normal distribution in which conditional independence relations of the random vector are encoded in a graph. Testing the hypothesis that a Gaussian graphical model is associated to either a graph or a specific subgraph corresponds to a composite hypothesis test in the Normal model. However, the standard likelihood ratio test for this problem has both poor power and size, and is only suitable if the sample siz...    »
 
Subject:
MAT Mathematik 
DDC:
510 Mathematik 
Advisor:
Mathias Drton 
Date of acceptation:
27.05.2021 
Year:
2021 
Quarter:
2. Quartal 
Year / month:
2021-05 
Month:
May 
Pages:
71 
Language:
en 
University:
Technische Universität München 
Faculty:
Fakultät für Mathematik 
TUM Institution:
Lehrstuhl für Mathematische Statistik