Journal Article10.1016/0167-9473(93)E0054-8
BIFROST—block recursive models induced from relevant knowledge, observations, and statistical techniques
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TL;DR: The theoretical background for a program for establishing expert systems on the basis of observations and expert knowledge and various model selection methods for automatic model selection are presented.
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About: This article is published in Computational Statistics & Data Analysis. The article was published on 01 Feb 1995. The article focuses on the topics: Expert system & Model selection.
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References
A new look at the statistical model identification
TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
Gideon Schwarz
- 01 Jan 2005
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
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Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
David Madigan,Adrian E. Raftery +1 more
TL;DR: In this article, the authors consider the problem of model selection and accounting for model uncertainty in high-dimensional contingency tables, motivated by expert system applications, and propose a panacea by the standard Bayesian formalism that averages the posterior distributions of the quantity of interest under each of the models, weighted by their posterior model probabilities.
1.4K