Abstract

Conditionally specified statistical models are frequently constructed from conditional one-parameter exponential family distributions. One way to formulate such a model is to specify the dependence structure among random variables through the use of a Markov random field. When this is done, a common assumption is that dependence is expressed only through pairs of random variables, the 'pairwise-only dependence' assumption. Using a Markov random field structure and the pairwise-only dependence assumption, Besag (1974) formulated exponential family 'auto-models', and showed the form that conditional one-parameter exponential family densities must have in such models. We extend those results under relaxation of the pairwise-only dependence assumption, and give a necessary form for conditional one-parameter exponential family densities under more general conditions of multiway dependence.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.