Next Article in Journal
Infinite Excess Entropy Processes with Countable-State Generators
Previous Article in Journal
Ensemble Entropy for Monitoring Network Design
Article Menu

Export Article

Open AccessArticle
Entropy 2014, 16(3), 1376-1395; doi:10.3390/e16031376

Bayesian Test of Significance for Conditional Independence: The Multinomial Model

Instituto de Matemática e Estatística, Universidade de São Paulo (IME-USP) Rua do Matão, 1010, Cidade Universitária, São Paulo, SP/Brasil
*
Author to whom correspondence should be addressed.
Received: 3 December 2013 / Revised: 21 February 2014 / Accepted: 5 March 2014 / Published: 7 March 2014
View Full-Text   |   Download PDF [373 KB, uploaded 24 February 2015]   |  

Abstract

Conditional independence tests have received special attention lately in machine learning and computational intelligence related literature as an important indicator of the relationship among the variables used by their models. In the field of probabilistic graphical models, which includes Bayesian network models, conditional independence tests are especially important for the task of learning the probabilistic graphical model structure from data. In this paper, we propose the full Bayesian significance test for tests of conditional independence for discrete datasets. The full Bayesian significance test is a powerful Bayesian test for precise hypothesis, as an alternative to the frequentist’s significance tests (characterized by the calculation of the p-value). View Full-Text
Keywords: hypothesis testing; probabilistic graphical models hypothesis testing; probabilistic graphical models
Figures

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

de Morais Andrade, P.; Stern, J.M.; de Bragança Pereira, C.A. Bayesian Test of Significance for Conditional Independence: The Multinomial Model. Entropy 2014, 16, 1376-1395.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top