andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1855 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Guy Freeman writes: I thought you’d all like to know that Stan was used and referenced in a peer-reviewed Rapid Communications paper on influenza. Thank you for this excellent modelling language and sampler, which made it possible to carry out this work quickly! I haven’t actually read the paper, but I’m happy to see Stan getting around like that.
sentIndex sentText sentNum sentScore
1 Guy Freeman writes: I thought you’d all like to know that Stan was used and referenced in a peer-reviewed Rapid Communications paper on influenza. [sent-1, score-0.782]
2 Thank you for this excellent modelling language and sampler, which made it possible to carry out this work quickly! [sent-2, score-1.137]
3 I haven’t actually read the paper, but I’m happy to see Stan getting around like that. [sent-3, score-0.674]
wordName wordTfidf (topN-words)
[('freeman', 0.335), ('stan', 0.323), ('referenced', 0.306), ('modelling', 0.278), ('communications', 0.278), ('rapid', 0.266), ('sampler', 0.253), ('carry', 0.241), ('thank', 0.233), ('quickly', 0.201), ('language', 0.177), ('excellent', 0.169), ('paper', 0.155), ('guy', 0.15), ('happy', 0.15), ('haven', 0.148), ('possible', 0.113), ('getting', 0.112), ('around', 0.105), ('read', 0.096), ('made', 0.095), ('thought', 0.092), ('used', 0.089), ('actually', 0.081), ('like', 0.081), ('work', 0.064), ('know', 0.059), ('writes', 0.056), ('see', 0.049)]
simIndex simValue blogId blogTitle
same-blog 1 1.0 1855 andrew gelman stats-2013-05-13-Stan!
Introduction: Guy Freeman writes: I thought you’d all like to know that Stan was used and referenced in a peer-reviewed Rapid Communications paper on influenza. Thank you for this excellent modelling language and sampler, which made it possible to carry out this work quickly! I haven’t actually read the paper, but I’m happy to see Stan getting around like that.
2 0.28070459 1475 andrew gelman stats-2012-08-30-A Stan is Born
Introduction: 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 for expressing models and a different sampler for sampling from their posteriors. RStan is the R interface to Stan. Stan Home Page Stan’s home page is: http://mc-stan.org/ It links everything you need to get started running Stan from the command line, from R, or from C++, including full step-by-step install instructions, a detailed user’s guide and reference manual for the modeling language, and tested ports of most of the BUGS examples. Peruse the Manual If you’d like to learn more, the Stan User’s Guide and Reference Manual is the place to start.
3 0.21559866 1580 andrew gelman stats-2012-11-16-Stantastic!
Introduction: Richard McElreath writes: I’ve been translating a few ongoing data analysis projects into Stan code, mostly with success. The most important for me right now has been a hierarchical zero-inflated gamma problem. This a “hurdle” model, in which a bernoulli GLM produces zeros/nonzeros, and then a gamma GLM produces the nonzero values, using varying effects correlated with those in the bernoulli process. The data are 20 years of human foraging returns from a subsistence hunting population in Paraguay (the Ache), comprising about 15k hunts in total (Hill & Kintigh. 2009. Current Anthropology 50:369-377). Observed values are kilograms of meat returned to camp. The more complex models contain a 147-by-9 matrix of varying effects (147 unique hunters), as well as imputation of missing values. Originally, I had written the sampler myself in raw R code. It was very slow, but I knew what it was doing at least. Just before Stan version 1.0 was released, I had managed to get JAGS to do it a
4 0.19603889 1748 andrew gelman stats-2013-03-04-PyStan!
Introduction: 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 free and open-source. P.S. Because Stan is open-source, it of course would also be possible for people to translate Stan into Python, or to take whatever features they like from Stan and incorporate them into a Python package. That’s fine too. But we think it would make sense in addition for users to be able to run Stan directly from Python, in the same way that it can be run from R.
5 0.16647477 2291 andrew gelman stats-2014-04-14-Transitioning to Stan
Introduction: Kevin Cartier writes: I’ve been happily using R for a number of years now and recently came across Stan. Looks big and powerful, so I’d like to pick an appropriate project and try it out. I wondered if you could point me to a link or document that goes into the motivation for this tool (aside from the Stan user doc)? What I’d like to understand is, at what point might you look at an emergent R project and advise, “You know, that thing you’re trying to do would be a whole lot easier/simpler/more straightforward to implement with Stan.” (or words to that effect). My reply: For my collaborators in political science, Stan has been most useful for models where the data set is not huge (e.g., we might have 10,000 data points or 50,000 data points but not 10 million) but where the model is somewhat complex (for example, a model with latent time series structure). The point is that the model has enough parameters and uncertainty that you’ll want to do full Bayes (rather than some sort
7 0.14578873 2161 andrew gelman stats-2014-01-07-My recent debugging experience
8 0.13471478 2209 andrew gelman stats-2014-02-13-CmdStan, RStan, PyStan v2.2.0
9 0.13045543 1528 andrew gelman stats-2012-10-10-My talk at MIT on Thurs 11 Oct
10 0.12247431 2096 andrew gelman stats-2013-11-10-Schiminovich is on The Simpsons
11 0.1174057 2150 andrew gelman stats-2013-12-27-(R-Py-Cmd)Stan 2.1.0
12 0.11264388 1627 andrew gelman stats-2012-12-17-Stan and RStan 1.1.0
13 0.10890449 2124 andrew gelman stats-2013-12-05-Stan (quietly) passes 512 people on the users list
14 0.10875748 857 andrew gelman stats-2011-08-17-Bayes pays
15 0.10404509 1472 andrew gelman stats-2012-08-28-Migrating from dot to underscore
16 0.10176337 1576 andrew gelman stats-2012-11-13-Stan at NIPS 2012 Workshop on Probabilistic Programming
17 0.10002261 1036 andrew gelman stats-2011-11-30-Stan uses Nuts!
18 0.098529682 2035 andrew gelman stats-2013-09-23-Scalable Stan
19 0.095865585 1131 andrew gelman stats-2012-01-20-Stan: A (Bayesian) Directed Graphical Model Compiler
20 0.094280332 2231 andrew gelman stats-2014-03-03-Running into a Stan Reference by Accident
topicId topicWeight
[(0, 0.098), (1, 0.005), (2, -0.064), (3, 0.043), (4, 0.063), (5, 0.048), (6, 0.023), (7, -0.208), (8, -0.062), (9, -0.099), (10, -0.088), (11, -0.025), (12, -0.086), (13, -0.037), (14, 0.099), (15, -0.023), (16, -0.018), (17, 0.063), (18, -0.016), (19, 0.024), (20, -0.053), (21, -0.006), (22, -0.044), (23, -0.001), (24, 0.022), (25, -0.005), (26, 0.022), (27, -0.03), (28, -0.065), (29, 0.018), (30, 0.045), (31, 0.018), (32, 0.02), (33, -0.032), (34, -0.044), (35, 0.05), (36, 0.063), (37, 0.028), (38, -0.005), (39, -0.021), (40, 0.006), (41, 0.018), (42, 0.007), (43, -0.008), (44, -0.004), (45, -0.033), (46, 0.035), (47, -0.025), (48, -0.0), (49, 0.015)]
simIndex simValue blogId blogTitle
same-blog 1 0.95977682 1855 andrew gelman stats-2013-05-13-Stan!
Introduction: Guy Freeman writes: I thought you’d all like to know that Stan was used and referenced in a peer-reviewed Rapid Communications paper on influenza. Thank you for this excellent modelling language and sampler, which made it possible to carry out this work quickly! I haven’t actually read the paper, but I’m happy to see Stan getting around like that.
2 0.93329829 1748 andrew gelman stats-2013-03-04-PyStan!
Introduction: 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 free and open-source. P.S. Because Stan is open-source, it of course would also be possible for people to translate Stan into Python, or to take whatever features they like from Stan and incorporate them into a Python package. That’s fine too. But we think it would make sense in addition for users to be able to run Stan directly from Python, in the same way that it can be run from R.
3 0.9248625 1475 andrew gelman stats-2012-08-30-A Stan is Born
Introduction: 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 for expressing models and a different sampler for sampling from their posteriors. RStan is the R interface to Stan. Stan Home Page Stan’s home page is: http://mc-stan.org/ It links everything you need to get started running Stan from the command line, from R, or from C++, including full step-by-step install instructions, a detailed user’s guide and reference manual for the modeling language, and tested ports of most of the BUGS examples. Peruse the Manual If you’d like to learn more, the Stan User’s Guide and Reference Manual is the place to start.
4 0.89993215 712 andrew gelman stats-2011-05-14-The joys of working in the public domain
Introduction: Stan will make a total lifetime profit of $0, so we can’t be sued !
5 0.88738149 2124 andrew gelman stats-2013-12-05-Stan (quietly) passes 512 people on the users list
Introduction: Stan is alive and well. We’re up to 523 people on the users list . [We're sure there are many more than 523 actual users, since it's easy to download and use Stan directly without joining the list.] We’re working on a v2.1.0 release now and we hope to release it in within the next couple of weeks.
6 0.88519579 2150 andrew gelman stats-2013-12-27-(R-Py-Cmd)Stan 2.1.0
7 0.87168121 2209 andrew gelman stats-2014-02-13-CmdStan, RStan, PyStan v2.2.0
8 0.84047443 1576 andrew gelman stats-2012-11-13-Stan at NIPS 2012 Workshop on Probabilistic Programming
9 0.83790076 1580 andrew gelman stats-2012-11-16-Stantastic!
10 0.81724882 2161 andrew gelman stats-2014-01-07-My recent debugging experience
11 0.80700225 2318 andrew gelman stats-2014-05-04-Stan (& JAGS) Tutorial on Linear Mixed Models
12 0.80417627 1627 andrew gelman stats-2012-12-17-Stan and RStan 1.1.0
13 0.79393864 1036 andrew gelman stats-2011-11-30-Stan uses Nuts!
14 0.78688622 2096 andrew gelman stats-2013-11-10-Schiminovich is on The Simpsons
15 0.78403336 1472 andrew gelman stats-2012-08-28-Migrating from dot to underscore
16 0.78309953 2325 andrew gelman stats-2014-05-07-Stan users meetup next week
17 0.75469542 2291 andrew gelman stats-2014-04-14-Transitioning to Stan
18 0.6990934 2003 andrew gelman stats-2013-08-30-Stan Project: Continuous Relaxations for Discrete MRFs
19 0.69412977 2035 andrew gelman stats-2013-09-23-Scalable Stan
20 0.67785978 1131 andrew gelman stats-2012-01-20-Stan: A (Bayesian) Directed Graphical Model Compiler
topicId topicWeight
[(16, 0.054), (24, 0.076), (43, 0.05), (86, 0.032), (89, 0.36), (99, 0.264)]
simIndex simValue blogId blogTitle
1 0.98689479 1685 andrew gelman stats-2013-01-21-Class on computational social science this semester, Fridays, 1:00-3:40pm
Introduction: Sharad Goel, Jake Hofman, and Sergei Vassilvitskii are teaching this awesome class on computational social science this semester in the applied math department at Columbia. Here’s the course info . You should take this course. These guys are amazing.
2 0.94135356 1215 andrew gelman stats-2012-03-16-The “hot hand” and problems with hypothesis testing
Introduction: Gur Yaari writes : Anyone who has ever watched a sports competition is familiar with expressions like “on fire”, “in the zone”, “on a roll”, “momentum” and so on. But what do these expressions really mean? In 1985 when Thomas Gilovich, Robert Vallone and Amos Tversky studied this phenomenon for the first time, they defined it as: “. . . these phrases express a belief that the performance of a player during a particular period is significantly better than expected on the basis of the player’s overall record”. Their conclusion was that what people tend to perceive as a “hot hand” is essentially a cognitive illusion caused by a misperception of random sequences. Until recently there was little, if any, evidence to rule out their conclusion. Increased computing power and new data availability from various sports now provide surprising evidence of this phenomenon, thus reigniting the debate. Yaari goes on to some studies that have found time dependence in basketball, baseball, voll
3 0.93383127 2243 andrew gelman stats-2014-03-11-The myth of the myth of the myth of the hot hand
Introduction: Phil pointed me to this paper so I thought I probably better repeat what I wrote a couple years ago: 1. The effects are certainly not zero. We are not machines, and anything that can affect our expectations (for example, our success in previous tries) should affect our performance. 2. The effects I’ve seen are small, on the order of 2 percentage points (for example, the probability of a success in some sports task might be 45% if you’re “hot” and 43% otherwise). 3. There’s a huge amount of variation, not just between but also among players. Sometimes if you succeed you will stay relaxed and focused, other times you can succeed and get overconfidence. 4. Whatever the latest results on particular sports, I can’t see anyone overturning the basic finding of Gilovich, Vallone, and Tversky that players and spectators alike will perceive the hot hand even when it does not exist and dramatically overestimate the magnitude and consistency of any hot-hand phenomenon that does exist.
4 0.93316156 1953 andrew gelman stats-2013-07-24-Recently in the sister blog
Introduction: Would You Accept DNA From A Murderer?
5 0.92702079 459 andrew gelman stats-2010-12-09-Solve mazes by starting at the exit
Introduction: It worked on this one . Good maze designers know this trick and are careful to design multiple branches in each direction. Back when I was in junior high, I used to make huge mazes, and the basic idea was to anticipate what the solver might try to do and to make the maze difficult by postponing the point at which he would realize a path was going nowhere. For example, you might have 6 branches: one dead end, two pairs that form loops going back to the start, and one that is the correct solution. You do this from both directions and add some twists and turns, and there you are. But the maze designer aiming for the naive solver–the sap who starts from the entrance and goes toward the exit–can simplify matters by just having 6 branches: five dead ends and one winner. This sort of thing is easy to solve in the reverse direction. I’m surprised the Times didn’t do better for their special puzzle issue.
6 0.92387569 1756 andrew gelman stats-2013-03-10-He said he was sorry
7 0.90727079 1160 andrew gelman stats-2012-02-09-Familial Linkage between Neuropsychiatric Disorders and Intellectual Interests
8 0.90449584 1477 andrew gelman stats-2012-08-30-Visualizing Distributions of Covariance Matrices
9 0.87575132 833 andrew gelman stats-2011-07-31-Untunable Metropolis
same-blog 11 0.86933446 1855 andrew gelman stats-2013-05-13-Stan!
12 0.82283497 407 andrew gelman stats-2010-11-11-Data Visualization vs. Statistical Graphics
13 0.79840088 566 andrew gelman stats-2011-02-09-The boxer, the wrestler, and the coin flip, again
14 0.79217887 623 andrew gelman stats-2011-03-21-Baseball’s greatest fielders
15 0.78368449 1783 andrew gelman stats-2013-03-31-He’s getting ready to write a book
16 0.7800982 1320 andrew gelman stats-2012-05-14-Question 4 of my final exam for Design and Analysis of Sample Surveys
17 0.77608275 1991 andrew gelman stats-2013-08-21-BDA3 table of contents (also a new paper on visualization)
18 0.76967764 850 andrew gelman stats-2011-08-11-Understanding how estimates change when you move to a multilevel model
19 0.76386976 1839 andrew gelman stats-2013-05-04-Jesus historian Niall Ferguson and the improving standards of public discourse
20 0.76317573 231 andrew gelman stats-2010-08-24-Yet another Bayesian job opportunity