Bayesian

Bayesian statistics blogs

Books on Scala for statistical computing and data science

December 22, 2016
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Books on Scala for statistical computing and data science

Introduction People regularly ask me about books and other resources for getting started with Scala for statistical computing and data science. This post will focus on books, but it’s worth briefly noting that there are a number of other resources available, on-line and otherwise, that are also worth considering. I particularly like the Coursera course … Continue reading Books on Scala for statistical computing and data science

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Scala for Data Science [book review]

December 22, 2016
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Scala for Data Science [book review]

This post will review the book: Scala for Data Science, Bugnion, Packt, 2016. Disclaimer: This book review has not been solicited by the publisher (or anyone else) in any way. I purchased the review copy of this book myself. I have not received any benefit from the writing of this review. Introduction On this blog … Continue reading Scala for Data Science [book review]

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Bayesian assessment of null values

December 21, 2016
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Bayesian assessment of null values

A blog post by Christian Robert considered an ancient (2011!) article titled "Bayesian assessment of null values via parameter estimation and model comparison." Here I'll try to clarify the ideas from way back then through the lens of more recent diagr...

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Working with SBML using Scala

December 17, 2016
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Working with SBML using Scala

Introduction The Systems Biology Markup Language (SBML) is an XML-based format for representation and exchange of biochemical network models. SBML is supported by most systems biology modelling tools, allowing the export of a model in SBML from one tool and then reading in another tool. Because it offers a standard way of representing biochemical networks … Continue reading Working with SBML using Scala

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The Bayesian New Statistics: Hypothesis Testing, Estimation, Meta-Analysis, and Power Analysis from a Bayesian Perspective

December 16, 2016
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The Bayesian New Statistics: Hypothesis Testing, Estimation, Meta-Analysis, and Power Analysis from a Bayesian Perspective

Two conceptual distinctions in the practice of data analysis. Rows show point-value hypothesis testing versus estimating magnitude with uncertainty. Columns show frequentist versus Bayesian methods. Cells indicate the typical information provided by ea...

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Is it legitimate to view the data and then decide on a distribution for the dependent variable?

November 17, 2016
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An emailer asks, In Bayesian parameter estimation, is it legitimate to view the data and then decide on a distribution for the dependent variable? I have heard that this is not “fully Bayesian”. The shortest questions often probe some of the most d...

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Bayesian meta-analysis of two proportions in random control trials

November 3, 2016
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Bayesian meta-analysis of two proportions in random control trials

For an article that's accepted pending final revision (available here at OSF), I developed a Bayesian meta-analysis of two proportions in random control trials. This blog post summarizes and links to the complete R scripts.We consider scenarios in whic...

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Should researchers be correcting for multiple tests, even when they themselves did not run the tests, but all of the tests were run on the same data?

October 25, 2016
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A graduate student, named Caitlin Ducate, in my frequentist statistics class asks:In Criminal Justice, it's common to use large data sets like the Uniform Crime Report (UCR) or versions of the National Longitudinal Survey (NLS) because the nature of ...

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Posterior predictive distribution for multiple linear regression

October 22, 2016
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Suppose you've done a (robust) Bayesian multiple linear regression, and now you want the posterior distribution on the predicted value of \(y\) for some probe value of \( \langle x_1,x_2,x_3, ... \rangle \). That is, not the posterior distribution on t...

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Stop saying confidence intervals are "better" than p values

July 29, 2016
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Stop saying confidence intervals are "better" than p values

One of the common tropes one hears from advocates of confidence intervals is that they are superior, or should be preferred, to p values. In our paper "The Fallacy of Placing Confidence in Confidence Intervals", we outlined a number of interpretation p...

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