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Parsimony and Bayesian phylogenetics

Pablo A. Goloboff and Diego Pol

in Parsimony, Phylogeny, and Genomics

Published in print:
2006
Published Online:
September 2007
ISBN:
9780199297306
eISBN:
9780191713729
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199297306.003.0008
Subject:
Biology, Evolutionary Biology / Genetics

The intent of a statistically-based phylogenetic method is to estimate tree topologies and values of possibly relevant parameters, as well as the uncertainty inherent in those estimations. A method ... More


 Keeping Up to Date

Ken Binmore

in Playing for Real: Game Theory

Published in print:
2007
Published Online:
May 2007
ISBN:
9780195300574
eISBN:
9780199783748
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195300574.003.0013
Subject:
Economics and Finance, Microeconomics

This chapter is about Bayesian decision theory. It explains why game theorists model players' beliefs using subjective probability distributions, and how these beliefs are updated using Bayes' rule ... More


A Negative Answer

Erik J. Olsson

in Against Coherence: Truth, Probability, and Justification

Published in print:
2005
Published Online:
July 2005
ISBN:
9780199279999
eISBN:
9780191602665
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/0199279993.003.0007
Subject:
Philosophy, Metaphysics/Epistemology

A sustained argument is given showing that more coherence does not imply a higher likelihood of truth even in fortunate circumstances (independence, individual credibility) and in a ceteris paribus ... More


Bayesian Basics and the Scientific Hypothesis

Bradley E. Alger

in Defense of the Scientific Hypothesis: From Reproducibility Crisis to Big Data

Published in print:
2019
Published Online:
February 2021
ISBN:
9780190881481
eISBN:
9780190093761
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780190881481.003.0006
Subject:
Neuroscience, Techniques

This chapter covers the basics of Bayesian statistics, emphasizing the conceptual framework for Bayes’ Theorem. It works through several iterations of the theorem to demonstrate how the same equation ... More


The Author Problem: Bayesian Inference with Two Hypotheses

Therese M. Donovan and Ruth M. Mickey

in Bayesian Statistics for Beginners: a step-by-step approach

Published in print:
2019
Published Online:
July 2019
ISBN:
9780198841296
eISBN:
9780191876820
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198841296.003.0005
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies

The “Author Problem” provides a concrete example of Bayesian inference. This chapter draws on work by Frederick Mosteller and David Wallace, who used Bayesian inference to assign authorship for ... More


Bayesian Treatments of Neuroimaging Data

Will Penny and Karl Friston

in Bayesian Brain: Probabilistic Approaches to Neural Coding

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262042383
eISBN:
9780262294188
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262042383.003.0005
Subject:
Neuroscience, Disorders of the Nervous System

This chapter describes the application of Bayesian methods to neuroimaging data. First, it introduces a functional magnetic resonance imaging (fMRI) data set that is analysed using posterior ... More


Entropy Regularization

Grandvalet Yves and Bengio Yoshua

in Semi-Supervised Learning

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262033589
eISBN:
9780262255899
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262033589.003.0009
Subject:
Computer Science, Machine Learning

This chapter promotes the use of entropy regularization as a means to benefit from unlabeled data in the framework of maximum a posteriori estimation. The learning criterion is derived from clearly ... More


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