Multiple mutual informations and multiple interactions in frequency data
TLDR
The concept of semi-independence is introduced as a finer one of the concept of independence in the ordinary sense, and is used to interpret various multiple interactions of frequency data with general n -way.Abstract:
McGill's multiple mutual informations are useful to systematically describe multiple interactions of frequency data with general n -way The asymptotic behaviour of the maximum likelihood estimators of them is analysed in terms of mutually independent X 2 -distributions On the basis of the results, the concept of semi-independence is introduced as a finer one of the concept of independence in the ordinary sense, and is used to interpret various multiple interactionsread more
Citations
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Journal ArticleDOI
Measuring the knowledge base of an economy in terms of triple-helix relations among 'technology, organization, and territory'
TL;DR: In this article, the authors combine the perspective of regional economics on the interrelationships among technology, organization, and territory with the triple-helix model, and offer the mutual information in three dimensions as an indicator of the configuration.
Dissertation
Machine Learning Based on Attribute Interactions
TL;DR: The present work shows that mutual information, information gain, correlation, attribute importance, association and many other concepts, are all merely special cases of the above principle.
Book
Computational analysis of the synergy among multiple interacting genes
TL;DR: An information‐theoretic analysis is presented that provides a quantitative measure of the multivariate synergy and decomposes sets of genes into submodules each of which contains synergistically interacting genes.
Book ChapterDOI
Analyzing Attribute Dependencies
Aleks Jakulin,Ivan Bratko +1 more
TL;DR: This paper formally defines the degree of interaction between attributes through the deviation of the best possible “voting” classifier from the true relation between the class and the attributes in a domain, and proposes a practical heuristic for detecting attribute interactions, called interaction gain.
Proceedings ArticleDOI
Testing the significance of attribute interactions
Aleks Jakulin,Ivan Bratko +1 more
TL;DR: The Kirkwood superposition approximation for constructing part-to-whole approximations is proposed and it is confirmed that the P-values computed with the assumption of the asymptotic X2 distribution closely match those obtained with the boot-strap.
References
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TL;DR: In this article, the authors consider statistical mechanics as a form of statistical inference rather than as a physical theory, and show that the usual computational rules, starting with the determination of the partition function, are an immediate consequence of the maximum-entropy principle.
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TL;DR: Algebra of Vectors and Matrices, Probability Theory, Tools and Techniques, and Continuous Probability Models.
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Linear Statistical Inference and its Applications
P. G. Moore,C. Radhakrishna Rao +1 more
TL;DR: The theory of least squares and analysis of variance has been studied in the literature for a long time, see as mentioned in this paper for a review of some of the most relevant works. But the main focus of this paper is on the analysis of variance.