In statistics, the use of Bayes factors is a Bayesian alternative to classical hypothesis testing. Bayesian model comparison is a method of modelâ€¦Â (More)

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Highly Cited

2014

Highly Cited

2014

The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental resultsâ€¦Â (More)

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Highly Cited

2012

Highly Cited

2012

Bayes factors have been advocated as superior to p-values for assessing statistical evidence in data. Despite the advantages ofâ€¦Â (More)

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Highly Cited

2005

Highly Cited

2005

Ways of obtaining approximate Bayes factors for generalised linear models are described, based on the Laplace method forâ€¦Â (More)

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2005

2005

- Gonzalo GarÄ‡Ä±a-Donato, Ming-Hui Chen, Ming-Hui Chen
- 2005

The Bayes factor is a popular criterion in Bayesian model selection. Due to the lack of symmetry of the prior predictiveâ€¦Â (More)

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2003

2003

Clustering by maximizing the dependency between (margin) groupings or partitionings of co-occurring data pairs is studied. Weâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

Mixture models, in which a probability distribution is represented as a linear superposition of component distributions, areâ€¦Â (More)

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Highly Cited

1998

Highly Cited

1998

- Nir Friedman
- UAI
- 1998

In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this areaâ€¦Â (More)

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Highly Cited

1998

Highly Cited

1998

- Chris Fraley, Adrian E. Raftery
- Comput. J.
- 1998

We consider the problem of determining the structure of clustered data, without prior knowledge of the number of clusters or anyâ€¦Â (More)

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Highly Cited

1993

Highly Cited

1993

Ways of obtaining approximate Bayes factors for generalized linear models are described, based on the Laplace method forâ€¦Â (More)

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Review

1993

Review

1993

In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor ofâ€¦Â (More)

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