The Markov basis of $K_{3,N}$
Johannes Rauh, Seth Sullivant
TL;DR
This paper details the method to compute a Markov basis for the binary graphical model of the complete bipartite graph K_{3,N}, illustrating the application of toric fiber product theory.
Contribution
It introduces a systematic approach to derive Markov bases for K_{3,N} using toric fiber product theory, expanding computational tools in algebraic statistics.
Findings
Explicit Markov basis for K_{3,N} derived
Computational methods align with theoretical predictions
Illustrates application of toric fiber product theory
Abstract
This document explains how to obtain a Markov basis of the graphical model of the complete bipartite graph with binary nodes. The computations illustrate the theory developed in arXiv:1404.6392 that explains how to compute Markov bases of toric fiber products.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopological and Geometric Data Analysis · Algorithms and Data Compression · Advanced Combinatorial Mathematics