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Highly Cited

2016

Highly Cited

2016

Bayes factors provide a symmetrical measure of evidence for one model versus another (e.g. H1 versus H0) in order to relate… Expand

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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 results… Expand

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Highly Cited

2012

Highly Cited

2012

Bayes factors have been advocated as superior to pp-values for assessing statistical evidence in data. Despite the advantages of… Expand

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Highly Cited

2009

Highly Cited

2009

A Bayesian approach to model comparison based on the integrated or marginal likelihood is considered, and applications to linear… Expand

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Highly Cited

2005

Highly Cited

2005

We present a novel approach to understanding the concepts of the theory of rough sets in terms of the inverse probabilities… Expand

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Highly Cited

2005

Highly Cited

2005

Traditionally, the use of Bayes factors has required the specification of proper prior distributions on model parameters that are… Expand

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Highly Cited

2004

Highly Cited

2004

In many multivariate domains, we are interested in analyzing the dependency structure of the underlying distribution, e.g… Expand

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Highly Cited

1999

Highly Cited

1999

I would like to thank David L. Weakliem (1999 [this issue]) for a thought-provoking discussion of the basis of the Bayesian… Expand

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Highly Cited

1996

Highly Cited

1996

SUMMARY Ways of obtaining approximate Bayes factors for generalised linear models are described, based on the Laplace method for… Expand

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Highly Cited

1992

Highly Cited

1992

Although Bayesian analysis has been in use since Laplace, the Bayesian method of model-comparison has only recently been… Expand

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