Posts Tagged ‘ Bayesian ’

Beginners Exercise: Bayesian Computation with Stan and Farmer Jöns

January 14, 2017
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Beginners Exercise: Bayesian Computation with Stan and Farmer Jöns

Over the last two years I’ve occasionally been giving a very basic tutorial to Bayesian statistics using R and Stan. At the end of the tutorial I hand out an exercise for those that want to flex their newly acquired skills. I call this exercise Bay...

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Subjectivity in statistics

December 15, 2016
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Andrew Gelman on subjectivity in statistics: Bayesian methods are often characterized as “subjective” because the user must choose a prior distribution, that is, a mathematical expression of prior information. The prior distribution requires information and user input, that’s for sure, but I don’t see this as being any more “subjective” than other aspects of a […]

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Cute Gibbs sampling for rounded observations

November 1, 2016
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Cute Gibbs sampling for rounded observations

I was attending a course of Bayesian Statistics where this problem showed up: There is a number of individuals, say 12, who take a pass/fail test 15 times. For each individual we have recorded the number of passes, which can go from 0 to 15. Because of confidentiality issues, we are presented with rounded-to-the-closest-multiple-of-3 data … Continue reading "Cute Gibbs sampling for rounded observations"

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The Bayesian approach to ridge regression

October 30, 2016
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The Bayesian approach to ridge regression

In a previous post, we demonstrated that ridge regression (a form of regularized linear regression that attempts to shrink the beta coefficients toward zero) can be super-effective at combating overfitting and lead to a greatly more generalizable model. This approach… Continue reading →

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Notes from 4th Bayesian Mixer Meetup

October 4, 2016
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Notes from 4th Bayesian Mixer Meetup

Last Tuesday we got together for the 4th Bayesian Mixer Meetup. Product Madness kindly hosted us at their offices in Euston Square. About 50 Bayesians came along; the biggest turn up thus far, including developers of PyMC3 (Peadar Coyle) and Stan (Mich...

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Fitting a distribution in Stan from scratch

September 27, 2016
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Fitting a distribution in Stan from scratch

Last week the French National Institute of Health and Medical Research (Inserm) organised with the Stan Group a training programme on Bayesian Inference with Stan for Pharmacometrics in Paris. Daniel Lee and Michael Betancourt, who run the course over ...

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Bayesian Bootstrap: The Movie + Some Highlights from UseR! 2016

July 20, 2016
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Not surprisingly, this year’s UseR! conference was a great event with heaps of talented researchers and R-developers showing off the latest and greatest R packages. (A surprise visit from Donald Knuth didn’t hurt either.) What was extra great thi...

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Notes from 3rd and 3.5th Bayesian Mixer Meetup

July 5, 2016
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Notes from 3rd and 3.5th Bayesian Mixer Meetup

Two Bayesian Mixer meet-ups in a row. Can it get any better?Our third 'regular' meeting took place at Cass Business School on 24 June. Big thanks to Pietro and Andreas, who supported us from Cass. The next day, Jon Sedar of Applied AI, managed to arran...

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Notes from 2nd Bayesian Mixer Meetup

April 19, 2016
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Notes from 2nd Bayesian Mixer Meetup

Last Friday the 2nd Bayesian Mixer Meetup (@BayesianMixer) took place at Cass Business School, thanks to Pietro Millossovich and Andreas Tsanakas, who helped to organise the event.Bayesian Mixer at CassFirst up was Davide De March talking about the cha...

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bayesboot: An R package for doing the Bayesian bootstrap

February 19, 2016
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bayesboot: An R package for doing the Bayesian bootstrap

I recently wrapped up a version of my R function for easy Bayesian bootstrappin’ into the package bayesboot. This package implements a function, also named bayesboot, which performs the Bayesian bootstrap introduced by Rubin in 1981. The Bayesian ...

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