andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1716 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: Burak Bayramli writes: I wanted to inform you on iPython Notebook technology – allowing markup, Python code to reside in one document. Someone ported one of your examples from ARM . iPynb file is actually a live document, can be downloaded and reran locally, hence change of code on document means change of images, results. Graphs (as well as text output) which are generated by the code, are placed inside the document automatically. No more referencing image files seperately. For now running notebooks locally require a notebook server, but that part can live “on the cloud” as part of an educational software. Viewers, such as nbviewer.ipython.org, do not even need that much, since all recent results of a notebook are embedded in the notebook itself. A lot of people are excited about this; Also out of nowhere, Alfred P. Sloan Foundation dropped a $1.15 million grant on the developers of ipython which provided some extra energy on the project. Cool. We’ll have to do that ex
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1 Burak Bayramli writes: I wanted to inform you on iPython Notebook technology – allowing markup, Python code to reside in one document. [sent-1, score-0.445]
2 iPynb file is actually a live document, can be downloaded and reran locally, hence change of code on document means change of images, results. [sent-3, score-0.944]
3 Graphs (as well as text output) which are generated by the code, are placed inside the document automatically. [sent-4, score-0.588]
4 For now running notebooks locally require a notebook server, but that part can live “on the cloud” as part of an educational software. [sent-6, score-1.296]
5 org, do not even need that much, since all recent results of a notebook are embedded in the notebook itself. [sent-9, score-1.092]
6 A lot of people are excited about this; Also out of nowhere, Alfred P. [sent-10, score-0.093]
7 15 million grant on the developers of ipython which provided some extra energy on the project. [sent-12, score-0.701]
8 It shouldn’t be too hard if we just discretize the arsenic and distance variables into something like 50 categories each. [sent-15, score-0.423]
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Introduction: Burak Bayramli writes: I wanted to inform you on iPython Notebook technology – allowing markup, Python code to reside in one document. Someone ported one of your examples from ARM . iPynb file is actually a live document, can be downloaded and reran locally, hence change of code on document means change of images, results. Graphs (as well as text output) which are generated by the code, are placed inside the document automatically. No more referencing image files seperately. For now running notebooks locally require a notebook server, but that part can live “on the cloud” as part of an educational software. Viewers, such as nbviewer.ipython.org, do not even need that much, since all recent results of a notebook are embedded in the notebook itself. A lot of people are excited about this; Also out of nowhere, Alfred P. Sloan Foundation dropped a $1.15 million grant on the developers of ipython which provided some extra energy on the project. Cool. We’ll have to do that ex
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Introduction: I want a graph-paper-style notebook, ideally something lightweight—I’m looking to make notes, not art drawings—and not too large. I’m currently using a 17 x 22 cm notebook, which is a fine size. It also has pretty small squares, which I like. My problem with the notebook I have now is that the ink is too heavy—that is, the lines are too dark. I want very faint lines, just visible enough to be used as guides but not so heavy that to be overwhelming. The notebooks I see in the stores all have pretty dark lines. Any suggestions?
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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
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Introduction: Govind Manian writes: I wanted to pass along a fragment from Lichtenberg’s Waste Books — which I am finding to be great stone soup — that reminded me of God is in Every Leaf : To the wise man nothing is great and nothing small…I believe he could write treatises on keyholes that sounded as weighty as a jus naturae and would be just as instructive. As the few adepts in such things well know, universal morality is to be found in little everyday penny-events just as much as in great ones. There is so much goodness and ingenuity in a raindrop that an apothecary wouldn’t let it go for less than half-a-crown… (Notebook B, 33)
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Introduction: 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 any problems on the mailing lists or at the e-mails linked on the home page (please don’t use this web page). The full release notes follow. (R)Stan Version 1.1.0 Release Notes =================================== -- Backward Compatibility Issue * Categorical distribution recoded to match documentation; it now has support {1,...,K} rather than {0,...,K-1}. * (RStan) change default value of permuted flag from FALSE to TRUE for Stan fit S4 extract() method -- New Features * Conditional (if-then-else) statements * While statements -- New Functions * generalized multiply_lower_tri
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Introduction: OK, so this sort of thing happens sometimes. I was working on a new idea (still working on it; if it ultimately works out—or if it doesn’t—I’ll let you know) and as part of it I was fitting little models in Stan, in a loop. I thought it would make sense to start with linear regression with normal priors and known data variance, because then the exact solution is Gaussian and I can also work with the problem analytically. So I programmed up the algorithm and, no surprise, it didn’t work. I went through my R code, put in print statements here and there, and cleared out bug after bug until at least it stopped crashing. But the algorithm still wasn’t doing what it was supposed to do. So I decided to do something simpler, and just check that the Stan linear regression gave the same answer as the analytic posterior distribution: I ran Stan for tons of iterations, then computed the sample mean and variance of the simulations. It was an example with two coefficients—I’d originally cho
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