The Stan Development Team is happy to announce that Stan 1.3.0 and RStan 1.3.0 are available for download. Follow the links on: Stan home page: http://mc-stan.org/ Please let us know if you have problems updating. Here’s the full set of release notes. v1.3.0 (12 April 2013) ====================================================================== Enhancements ———————————- Modeling Language * forward sampling (random [...]
Archive of posts tagged R
Stan at Google this Thurs and at Berkeley this Fri noon
Michael Betancourt will be speaking at Google and at the University of California, Berkeley. The Google talk is closed to outsiders (but if you work at Google, you should go!); the Berkeley talk is open to all: Friday March 22, 12:10 pm, Evans Hall 1011. Title of talk: Stan: Practical Bayesian Inference with Hamiltonian Monte [...]
How do I make my graphs?
Someone who wishes to remain anonymous writes:
Cool GSS training video! And cumulative file 1972-2012!
Felipe Osorio made the above video to help people use the General Social Survey and R to answer research questions in social science. Go for it! Meanwhile, Tom Smith reports: The initial release of the General Social Survey (GSS), cumulative file for 1972-2012 is now on our website. Codebooks and copies of questionnaires will be [...]
Stan 1.2.0 and RStan 1.2.0
Stan 1.2.0 and RStan 1.2.0 are now available for download. See: http://mc-stan.org/ Here are the highlights. Full Mass Matrix Estimation during Warmup Yuanjun Gao, a first-year grad student here at Columbia (!), built a regularized mass-matrix estimator. This helps for posteriors with high correlation among parameters and varying scales. We’re still testing this ourselves, so [...]
Stan in L.A. this Wed 3:30pm
Michael Betancourt will be speaking at UCLA: The location for refreshment is in room 51-254 CHS at 3:00 PM. The place for the seminar is at CHS 33-105A at 3:30pm – 4:30pm, Wed 6 Mar. ["CHS" stands for Center for Health Sciences, the building of the UCLA schools of medicine and public health. Here's a [...]
PyStan!
Stan is written in C++ and can be run from the command line and from R. We’d like for Python users to be able to run Stan as well. If anyone is interested in doing this, please let us know and we’d be happy to work with you on it. Stan, like Python, is completely [...]
Rcpp class in Sat 9 Mar in NYC
Join Dirk Eddelbuettel for six hours of detailed and hands-on instructions and discussions around Rcpp, RInside, RcppArmadillo, RcppGSL and other packages . . . Rcpp has become the most widely-used language extension for R. Currently deployed by 103 CRAN packages and a further 10 BioConductor packages, it permits users and developers to pass “whole R [...]
A must-read paper on statistical analysis of experimental data
Russ Lyons points to an excellent article on statistical experimentation by Ron Kohavi, Alex Deng, Brian Frasca, Roger Longbotham, Toby Walker, Ya Xu, a group of software engineers (I presume) at Microsoft. Kohavi et al. write: Online controlled experiments are often utilized to make data-driven decisions at Amazon, Microsoft . . . deployment and mining [...]
Partial least squares path analysis
Wayne Folta writes:
The new Stan 1.1.1, featuring Gaussian processes!
We just released Stan 1.1.1 and RStan 1.1.1 As usual, you can find download and install instructions at: http://mc-stan.org/ This is a patch release and is fully backward compatible with Stan and RStan 1.1.0. The main thing you should notice is that the multivariate models should be much faster and all the bugs reported for [...]
R package for Bayes factors
Richard Morey writes: You and your blog readers may be interested to know that a we’ve released a major new version of the BayesFactor package to CRAN. The package computes Bayes factors for linear mixed models and regression models. Of course, I’m aware you don’t like point-null model comparisons, but the package does more than [...]
The statistics software signal
Tyler Cowen links to a post by Sean Taylor, who writes the following about users of R: You are willing to invest in learning something difficult. You do not care about aesthetics, only availability of packages and getting results quickly. To me, R is easy and Sas is difficult. I once worked with some students [...]
Stan and RStan 1.1.0
We’re happy to announce the availability of Stan and RStan versions 1.1.0, which are general tools for performing model-based Bayesian inference using the no-U-turn sampler, an adaptive form of Hamiltonian Monte Carlo. Information on downloading and installing and using them is available as always from Stan Home Page: http://mc-stan.org/ Let us know if you have [...]
An epithet I can live with
Here. Indeed, I’d much rather be a legend than a myth. I just want to clarify one thing. Walter Hickey writes: [Antony Unwin and Andrew Gelman] collaborated on this presentation where they take a hard look at what’s wrong with the recent trends of data visualization and infographics. The takeaway is that while there have [...]
Is it meaningful to talk about a probability of “65.7%” that Obama will win the election?
The other day we had a fun little discussion in the comments section of the sister blog about the appropriateness of stating forecast probabilities to the nearest tenth of a percentage point. It started when Josh Tucker posted this graph from Nate Silver: My first reaction was: this looks pretty but it’s hyper-precise. I’m a [...]
Stan is fast
10,000 iterations for 4 chains on the (precompiled) efficiently-parameterized 8-schools model:
A Stan is Born
Stan 1.0.0 and RStan 1.0.0 It’s official. The Stan Development Team is happy to announce the first stable versions of Stan and RStan. What is (R)Stan? Stan is an open-source package for obtaining Bayesian inference using the No-U-Turn sampler, a variant of Hamiltonian Monte Carlo. It’s sort of like BUGS, but with a different language [...]
Moving beyond hopeless graphics
I was at a talk awhile ago where the speaker presented tables with 4, 5, 6, even 8 significant digits even though, as is usual, only the first or second digit of each number conveyed any useful information. A graph would be better, but even if you’re too lazy to make a plot, a bit [...]
Decline Effect in Linguistics?
Josef Fruehwald writes: In the past few years, the empirical foundations of the social sciences, especially Psychology, have been coming under increased scrutiny and criticism. For example, there was the New Yorker piece from 2010 called “The Truth Wears Off” about the “decline effect,” or how the effect size of a phenomenon appears to decrease [...]
Will Tiger Woods catch Jack Nicklaus? And a discussion of the virtues of using continuous data even if your goal is discrete prediction
I know next to nothing about golf. My mini-golf scores typically approach the maximum of 7 per hole, and I’ve never actually played macro-golf. I did publish a paper on golf once (A Probability Model for Golf Putting, with Deb Nolan), but it’s not so rare for people to publish papers on topics they know [...]
The first version of my “inference from iterative simulation using parallel sequences” paper!
From August 1990. It was in the form of a note sent to all the people in the statistics group of Bell Labs, where I’d worked that summer. To all: Here’s the abstract of the work I’ve done this summer. It’s stored in the file, /fs5/gelman/abstract.bell, and copies of the Figures 1-3 are on Trevor’s [...]
chartsnthings !
Yair pointed me to this awesome blog of how the NYT people make their graphs. This blows away all other stat graphics blogs (including this one). Lots of examples from mockup to first tries to final version. I recognize a lot of what they’re doing from my own experience. Also from my experience it’s hard [...]
Google Translate for code, and an R help-list bot
What we did in our Stan meeting yesterday: Some discussion of revision of the Nuts paper, some conversations about parameterizations of categorical-data models, plans for the R interface, blah blah blah. But also, I had two exciting new ideas! Google Translate for code Wouldn’t it be great if Google Translate could work on computer languages? [...]
Lessons learned from a recent R package submission
R has zillions of packages, and people are submitting new ones each day. The volunteers who keep R going are doing an incredibly useful service to the profession, and they’re busy. A colleague sends in some suugestions based on a recent experience with a package update: 1. Always use the R dev version to write [...]