Posts Tagged ‘ Statistical computing ’

Reduced-dimensionality parameterizations for linear models with interactions

June 21, 2016
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After seeing this post by Matthew Wilson on a class of regression models called “factorization machines,” Aki writes: In a typical machine learning way, this is called “machine”, but it would be also a useful mode structure in Stan to make linear models with interactions, but with a reduced number of parameters. With a fixed […] The post Reduced-dimensionality parameterizations for linear models with interactions appeared first on Statistical Modeling,…

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Log Sum of Exponentials for Robust Sums on the Log Scale

June 11, 2016
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This is a public service announcement in the interest of more robust numerical calculations. Like matrix inverse, exponentiation is bad news. It’s prone to overflow or underflow. Just try this in R: > exp(-800) > exp(800) That’s not rounding error you see. The first one evaluates to zero (underflows) and the second to infinity (overflows). […] The post Log Sum of Exponentials for Robust Sums on the Log Scale appeared…

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Betancourt Binge (Video Lectures on HMC and Stan)

June 10, 2016
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Betancourt Binge (Video Lectures on HMC and Stan)

Even better than binging on Netflix, catch up on Michael Betancourt’s updated video lectures, just days after their live theatrical debut in Tokyo. Scalable Bayesian Inference with Hamiltonian Monte Carlo (YouTube, 1 hour) Some Bayesian Modeling Techniques in Stan (YouTube, 1 hour 40 minutes) His previous videos have received very good reviews and they’re only […] The post Betancourt Binge (Video Lectures on HMC and Stan) appeared first on Statistical…

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A Primer on Bayesian Multilevel Modeling using PyStan

June 9, 2016
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A Primer on Bayesian Multilevel Modeling using PyStan

Chris Fonnesbeck contributed our first PyStan case study (I wrote the abstract), in the form of a very nice Jupyter notebook. Daniel Lee and I had the pleasure of seeing him present it live as part of a course we were doing at Vanderbilt last week. A Primer on Bayesian Multilevel Modeling using PyStan This […] The post A Primer on Bayesian Multilevel Modeling using PyStan appeared first on Statistical…

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Stan workshop this Thurs NYC

June 6, 2016
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Jonah is speaking at the Bayesian Data Analysis meetup on Thursday night, “Stan Workshop. Life is precious: fix your sampling problems.” He’ll focus on common problems using MCMC and how to address them. For registration: http://www.m...

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Birthday analysis—Friday the 13th update, and some model checking

May 18, 2016
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Birthday analysis—Friday the 13th update, and some model checking

Carl Bialik and Andrew Flowers at fivethirtyeight.com (Nate Silver’s site) ran a story following up on our birthdays example—that time series decomposition of births by day, which is on the cover of the third edition of Bayesian Data Analysis using data from 1968-1988, and which then Aki redid using a new dataset from 2000-2014. Friday […] The post Birthday analysis—Friday the 13th update, and some model checking appeared first on…

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Point summary of posterior simulations?

May 14, 2016
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Luke Miratrix writes: ​In the applied stats class ​I’m teaching ​on​ hierarchical models I’m giving the students (a mix of graduate students, many from the education school, and undergrads) a taste of Stan. I have to give them some “standard” way to turn Stan output into a point estimate (though of course I’ll also explain […] The post Point summary of posterior simulations? appeared first on Statistical Modeling, Causal Inference,…

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Stochastic natural-gradient EP

April 22, 2016
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Yee Whye Teh sends along this paper with Leonard Hasenclever, Thibaut Lienart, Sebastian Vollmer, Stefan Webb, Balaji Lakshminarayanan, and Charles Blundell. I haven’t read it in detail but they not similarities to our “expectation propaga...

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A new idea for a science core course based entirely on computer simulation

April 21, 2016
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I happen to come across this post from 2011 that I like so much, I thought I’d say it again: Columbia College has for many years had a Core Curriculum, in which students read classics such as Plato (in translation) etc. A few years ago they created a Science core course. There was always some […] The post A new idea for a science core course based entirely on computer…

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Black Box Challenge

April 9, 2016
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Black Box Challenge

Georgy Cheremovskiy writes: I’m one of the organizers of an unusual reinforcement learning competition named Black Box Challenge. The conception is simple — one need to program an agent that can play a game with unknown rules. At each time step agent is given an environment state vector and has a few possible actions. The […] The post Black Box Challenge appeared first on Statistical Modeling, Causal Inference, and Social…

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