Bayesian

Bayesian statistics blogs

Bayesian workshops, June and August 2017

April 16, 2017
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Bayesian workshops, June and August 2017

Upcoming multi-day workshops in doing Bayesian data analysis (2017):June 5 - 9. Stats Camp, Albuquerque, New Mexico (USA). Taught by Prof. John Kruschke. June 12 - 16. Global School for Empirical Research Methods, St. Gallen, Switzerland. Taught by ...

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Trade-off of between-group and within-group variance (and implosive shrinkage)

April 8, 2017
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Background: Consider data that would traditionally be analyzed as single-factor ANOVA; that is, a continuous metric predicted variable, \(y\), and a nominal predictor, "Group." In particular, consider the data plotted as red dots here:A Bayesian approa...

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A foolish prior on consistency is the howling of shrunken minds

April 2, 2017
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A foolish prior on consistency is the howling of shrunken minds

(Photo from Professor Sylvain Fiset's web site.)Professor Sylvain Fiset has been using Bayesian methods (from DBDA2E)  to analyze short-term memory of dogs. In each experimental trial, a dog watched a human experimenter tuck away a treat in one of...

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MCMC as a Stream

April 1, 2017
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MCMC as a Stream

Introduction This weekend I’ve been preparing some material for my upcoming Scala for statistical computing short course. As part of the course, I thought it would be useful to walk through how to think about and structure MCMC codes, and in particular, how to think about MCMC algorithms as infinite streams of state. This material … Continue reading MCMC as a Stream

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Doggerel Doggies: The Generalized Linear Model

March 5, 2017
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Doggerel Doggies: The Generalized Linear Model

The opening "poem" from Chapter 15 of DBDA2E. The color coding explains the correspondence of metaphor to math.

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Workshops & courses doing Bayesian data analysis, June – Aug 2017

February 23, 2017
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Workshops & courses doing Bayesian data analysis, June – Aug 2017

Upcoming multi-day workshops in doing Bayesian data analysis (2017):June 5 - 9. Stats Camp, Albuquerque, New Mexico (USA). Taught by Prof. John Kruschke. June 12 - 16. Global School for Empirical Research Methods, St. Gallen, Switzerland. Taught by ...

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Interpreting Bayesian posterior distribution of a parameter: Is density meaningful?

February 19, 2017
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Interpreting Bayesian posterior distribution of a parameter: Is density meaningful?

Background: Suppose a researcher is interested in the Bayesian posterior distribution of a parameter, because the parameter is directly meaningful in the research domain. This occurs, for example, in psychometrics. Specifically, in item response theory...

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Equivalence testing (two one-sided test) and NHST compared with HDI and ROPE

February 16, 2017
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Equivalence testing (two one-sided test) and NHST compared with HDI and ROPE

In this blog post I show that frequentist equivalence testing (using the procedure of two one-sided tests: TOST) with null hypothesis significance testing (NHST) can produce conflicting decisions for the same parameter values, that is, TOST can accept ...

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The Bayesian New Statistics – finally published

February 8, 2017
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The Bayesian New Statistics – finally published

The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective.Abstract: In the practice of data analysis, there is a conceptual distinction between hypothesis testing, on the one hand, and es...

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A quick introduction to Apache Spark for statisticians

February 8, 2017
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A quick introduction to Apache Spark for statisticians

Introduction Apache Spark is a Scala library for analysing "big data". It can be used for analysing huge (internet-scale) datasets distributed across large clusters of machines. The analysis can be anything from the computation of simple descriptive statistics associated with the datasets, through to rather sophisticated machine learning pipelines involving data pre-processing, transformation, nonlinear model … Continue reading A quick introduction to Apache Spark for statisticians

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