Proof of a Conjecture of Drton, Sturmfels and Sullivant on the maximum likelihood degree of the Gaussian graphical model of a cycle

In this article, we compute the precise value of the maximum likelihood degree of the Gaussian graphical model of a cycle, confirming a conjecture due to Drton, Sturmfels and Sullivant.

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Publication Details

Journal
ArXiv.org
Published
2025-03-04
Primary Topic
Data Management and Algorithms
Type
article
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article

Proof of a Conjecture of Drton, Sturmfels and Sullivant on the maximum likelihood degree of the Gaussian graphical model of a cycle

Martin Vodička, Rodica Dinu
ArXiv.org
Data Management and Algorithms
article

Proof of a Conjecture of Drton, Sturmfels and Sullivant on the maximum likelihood degree of the Gaussian graphical model of a cycle

Martin Vodička, Rodica Dinu
article en

Abstract

In this article, we compute the precise value of the maximum likelihood degree of the Gaussian graphical model of a cycle, confirming a conjecture due to Drton, Sturmfels and Sullivant.

ArXiv.org
Openalex Percentile: Top 63%
Data Management and Algorithms
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Proof of a Conjecture of Drton, Sturmfels and Sullivant on the maximum likelihood degree of the Gaussian graphical model of a cycle — Martin Vodička, Rodica Dinu · ArXiv.org (2025) | TGRS Research Map | TGRS