Posts Tagged ‘ Bayesian statistics ’

Brexit polling: What went wrong?

June 24, 2016
By
Brexit polling:  What went wrong?

Commenter numeric writes: Since you were shilling for yougov the other day you might want to talk about their big miss on Brexit (off by 6% from their eve-of-election poll—remain up 2 on their last poll and leave up by 4 as of this posting). Fair enough: Had Yougov done well, I could use them […] The post Brexit polling: What went wrong? appeared first on Statistical Modeling, Causal Inference,…

Read more »

My talk tomorrow (Thurs) 10:30am at ICML in NYC

June 24, 2016
By

I’ll be speaking at the workshop on Data-Efficient Machine Learning. And here’s the schedule. I’ll be speaking on the following topic: Toward Routine Use of Informative Priors Bayesian statistics is typically performed using noninformative priors but the resulting inferences commonly make no sense and also can lead to computational problems as algorithms have to waste […] The post My talk tomorrow (Thurs) 10:30am at ICML in NYC appeared first on…

Read more »

YouGov uses Mister P for Brexit poll

June 21, 2016
By
YouGov uses Mister P for Brexit poll

Ben Lauderdale and Doug Rivers give the story: There has been a lot of noise in polling on the upcoming EU referendum. Unlike the polls before the 2015 General Election, which were in almost perfect agreement (though, of course, not particularly close to the actual outcome), this time the polls are in serious disagreement. Telephone […] The post YouGov uses Mister P for Brexit poll appeared first on Statistical Modeling,…

Read more »

Reduced-dimensionality parameterizations for linear models with interactions

June 21, 2016
By

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,…

Read more »

My week at ISBA (2)

June 17, 2016
By

I should add to my previous post that while there have been many very good talks, I thought two were incredibly good: David Spiegelhalter's Foundational lecture on Monday and Adrian Raftery's talk in a session on Bayesian Demography that was very inter...

Read more »

My week at ISBA

June 17, 2016
By

I've spent the last few days in beautiful Sardinia for the ISBA world conference. The place is outstanding, really beautiful, although it's kind of weird that there is no real town along the cost for miles and miles. Leaving Cagliari and driving for ov...

Read more »

The answer is the Edlin factor

June 13, 2016
By

Garnett McMillan writes: You have argued about the pervasive role of the Garden of Forking Paths in published research. Given this influence, do you think that it is sensible to use published research to inform priors in new studies? My reply: Yes, I think you can use published research but in doing so you should […] The post The answer is the Edlin factor appeared first on Statistical Modeling, Causal…

Read more »

Stan makes Euro predictions! (now with data and code so you can fit your own, better model)

June 11, 2016
By
Stan makes Euro predictions! (now with data and code so you can fit your own, better model)

Leonardo Egidi writes: Inspired by your world cup model I fitted in Stan a model for the Euro Cup which start today, with two Poisson distributions for the goals scored at every match by the two teams (perfect prediction for the first match!). Data and code are here. Here’s the model, and here are the […] The post Stan makes Euro predictions! (now with data and code so you can…

Read more »

Betancourt Binge (Video Lectures on HMC and Stan)

June 10, 2016
By
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…

Read more »

A Primer on Bayesian Multilevel Modeling using PyStan

June 9, 2016
By
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…

Read more »


Subscribe

Email:

  Subscribe