AbstractWe provide a polyhedral description of the conditions for the existence of the maximum likelihood estimate (MLE) for a hierarchical log-linear model. The MLE exists if and only if the observed margins lie in the relative interior of the marginal cone. Using this description, we give an algorithm for determining if the MLE exists. If the tree width is bounded, the algorithm runs in polynomial time. We also perform a computational study of the case of three random variables under the no three-factor effect model
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
We use reversible jump Markov chain Monte Carlo methods (Green, 1995) to develop strategies for calc...
Asmussen & Edwards (1983) defined necessary and sufficient conditions for collapsibil-ity of a h...
AbstractWe provide a polyhedral description of the conditions for the existence of the maximum likel...
In this article, we combine results from the theory of linear exponential families, polyhedral geome...
Hierarchical log-linear models are essential tools used for relationship identification between vari...
Models defined by a set of conditional independence restrictions play an important role in statistic...
The codegree of a lattice polytope is the smallest integer dilate that contains a lattice point in t...
Non-response boundary solutions occur in log-linear models with non-ignorable non-response. We prove...
Key Words: exponential families; graphical models; stepwise Bayes It is well known that for certain ...
Abstract: When in a full exponential family the maximum likelihood estimate (MLE) does not exist, th...
In this paper, algorithms are described for obtaining the maximum likelihood estimates of the parame...
We study the problem of maximum likelihood estimation of densities that are log-concave and lie in t...
We study maximum likelihood estimation in Gaussian graphical models from a geometric point of view. ...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
We use reversible jump Markov chain Monte Carlo methods (Green, 1995) to develop strategies for calc...
Asmussen & Edwards (1983) defined necessary and sufficient conditions for collapsibil-ity of a h...
AbstractWe provide a polyhedral description of the conditions for the existence of the maximum likel...
In this article, we combine results from the theory of linear exponential families, polyhedral geome...
Hierarchical log-linear models are essential tools used for relationship identification between vari...
Models defined by a set of conditional independence restrictions play an important role in statistic...
The codegree of a lattice polytope is the smallest integer dilate that contains a lattice point in t...
Non-response boundary solutions occur in log-linear models with non-ignorable non-response. We prove...
Key Words: exponential families; graphical models; stepwise Bayes It is well known that for certain ...
Abstract: When in a full exponential family the maximum likelihood estimate (MLE) does not exist, th...
In this paper, algorithms are described for obtaining the maximum likelihood estimates of the parame...
We study the problem of maximum likelihood estimation of densities that are log-concave and lie in t...
We study maximum likelihood estimation in Gaussian graphical models from a geometric point of view. ...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
In categorical data analysis, log-linear models are widely used statistical tools for analyzing the ...
We use reversible jump Markov chain Monte Carlo methods (Green, 1995) to develop strategies for calc...
Asmussen & Edwards (1983) defined necessary and sufficient conditions for collapsibil-ity of a h...