On robust Gaussian graphical modelling

Daniel Vogel, Roland Fried

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

The objective of this exposition is to give an overview of the existing approaches to robust Gaussian graphical modelling. We start by thoroughly introducing Gaussian graphical models (also known as covariance selection models or concentration graph models) and then review the established, likelihood-based statistical theory (estimation, testing and model selection). Afterwards we describe robust methods and compare them to the classical approaches.
Original languageEnglish
Title of host publicationRecent Developments in Applied Probability and Statistics
Subtitle of host publicationDedicated to the Memory of Jürgen Lehn
EditorsLuc Devroye, Bulent Karasozen, Michael Kohler, Ralf Korn
PublisherPhysica-Verlag HD
Pages155-182
Number of pages28
ISBN (Electronic)978-3-7908-2598-5
ISBN (Print)978-3-7908-2597-8
DOIs
Publication statusPublished - 2010

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Vogel, D., & Fried, R. (2010). On robust Gaussian graphical modelling. In L. Devroye, B. Karasozen, M. Kohler, & R. Korn (Eds.), Recent Developments in Applied Probability and Statistics: Dedicated to the Memory of Jürgen Lehn (pp. 155-182). Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2598-5_7