DeepAI
Log In Sign Up

Quasi-independence models with rational maximum likelihood estimates

06/11/2020
by   Jane Ivy Coons, et al.
0

We classify the two-way independence quasi-independence models (or independence models with structural zeros) that have rational maximum likelihood estimators, or MLEs. We give a necessary and sufficient condition on the bipartite graph associated to the model for the MLE to be rational. In this case, we give an explicit formula for the MLE in terms of combinatorial features of this graph. We also use the Horn uniformization to show that for general log-linear models ℳ with rational MLE, any model obtained by restricting to a face of the cone of sufficient statistics of ℳ also has rational MLE.

READ FULL TEXT

page 1

page 2

page 3

page 4

09/16/2021

Families of polytopes with rational linear precision in higher dimensions

In this article we introduce a new family of lattice polytopes with rati...
06/01/2022

Rational partition models under iterative proportional scaling

In this work we investigate partition models, the subset of log-linear m...
01/30/2018

A Rational Distributed Process-level Account of Independence Judgment

It is inconceivable how chaotic the world would look to humans, faced wi...
06/04/2019

Quasi-automatic groups are asynchronously automatic

A quasi-automatic semigroup is a finitely generated semigroup with a rat...
12/19/2021

Marginal Independence Models

We impose rank one constraints on marginalizations of a tensor, given by...
05/19/2022

Classifying one-dimensional discrete models with maximum likelihood degree one

We propose a classification of all one-dimensional discrete statistical ...
02/02/2020

Hierarchical Aitchison-Silvey models for incomplete binary sample spaces

Multivariate sample spaces may be incomplete Cartesian products, when ce...