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The Maximum Likelihood Threshold of a Graph
The maximum likelihood threshold of a graph is the smallest number of data
points that guarantees that maximum likelihood estimates exist almost surely in
the Gaussian graphical model associated to the graph. We show that this graph
parameter is connected to the theory of combinatorial rigidity. In particular,
if the edge set of a graph is an independent set in the -dimensional
generic rigidity matroid, then the maximum likelihood threshold of is less
than or equal to . This connection allows us to prove many results about the
maximum likelihood threshold.Comment: Added Section 6 and Section
Sandwiching saturation number of fullerene graphs
The saturation number of a graph is the cardinality of any smallest
maximal matching of , and it is denoted by . Fullerene graphs are
cubic planar graphs with exactly twelve 5-faces; all the other faces are
hexagons. They are used to capture the structure of carbon molecules. Here we
show that the saturation number of fullerenes on vertices is essentially
Triangle-Free Penny Graphs: Degeneracy, Choosability, and Edge Count
We show that triangle-free penny graphs have degeneracy at most two, list
coloring number (choosability) at most three, diameter , and
at most edges.Comment: 10 pages, 2 figures. To appear at the 25th International Symposium on
Graph Drawing and Network Visualization (GD 2017
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