Posts Tagged ‘ Statistical computing ’

Could you say that again less clearly, please? A general-purpose data garbler for applications requiring confidentiality

May 13, 2018
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Ariel Rokem pointed me to this Python program by Bill Howe, Julia Stoyanovich, Haoyue Ping, Bernease Herman, and Matt Gee that will take your data matrix and produce a new data matrix that has the same size, shape, and general statistical properties but with none of the same actual numbers. The use case is when […] The post Could you say that again less clearly, please? A general-purpose data garbler…

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How about zero-excluding priors for hierarchical variance parameters to improve computation for full Bayesian inference?

May 4, 2018
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So. For awhile now we’ve moved away from the uniform (or, worse, inverse-gamma!) prior distributions for hierarchical variance parameters. We’ve done half-Cauchy, folded t, and other options; now we’re favoring unit half-normal. We also have boundary-avoiding priors for point estimates, so that in 8-schools-type problems, the posterior mode won’t be zero. Something like the gamma(2) […] The post How about zero-excluding priors for hierarchical variance parameters to improve computation for…

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The current state of the Stan ecosystem in R

April 24, 2018
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(This post is by Jonah) Last week I posted here about the release of version 2.0.0 of the loo R package, but there have been a few other recent releases and updates worth mentioning. At the end of the post I also include some general thoughts on R package development with Stan and the growing number of […] The post The current state of the Stan ecosystem in R appeared first on…

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Postdoc opportunity at AstraZeneca in Cambridge, England, in Bayesian Machine Learning using Stan!

April 19, 2018
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Here it is: Predicting drug toxicity with Bayesian machine learning models We’re currently looking for talented scientists to join our innovative academic-style Postdoc. From our centre in Cambridge, UK you’ll be in a global pharmaceutical environment, contributing to live projects right from the start. You’ll take part in a comprehensive training programme, including a focus […] The post Postdoc opportunity at AstraZeneca in Cambridge, England, in Bayesian Machine Learning using…

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You better check yo self before you wreck yo self

April 18, 2018
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You better check yo self before you wreck yo self

We (Sean Talts, Michael Betancourt, Me, Aki, and Andrew) just uploaded a paper (code available here) that outlines a framework for verifying that an algorithm for computing a posterior distribution has been implemented correctly. It is easy to use, straightforward to implement, and ready to be implemented as part of a Bayesian workflow. This type of […] The post You better check yo self before you wreck yo self appeared first…

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loo 2.0 is loose

April 16, 2018
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This post is by Jonah and Aki. We’re happy to announce the release of v2.0.0 of the loo R package for efficient approximate leave-one-out cross-validation (and more). For anyone unfamiliar with the package, the original motivation for its development is in our paper: Vehtari, A., Gelman, A., and Gabry, J. (2017). Practical Bayesian model evaluation […] The post loo 2.0 is loose appeared first on Statistical Modeling, Causal Inference, and…

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Generable: They’re building software for pharma, with Stan inside.

April 15, 2018
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Daniel Lee writes: We’ve just launched our new website. Generable is where precision medicine meets statistical machine learning. We are building a state-of-the-art platform to make individual, patient-level predictions for safety and efficacy of treatments. We’re able to do this by building Bayesian models with Stan. We currently have pilots with AstraZeneca, Sanofi, and University […] The post Generable: They’re building software for pharma, with Stan inside. appeared first on…

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Fitting a hierarchical model without losing control

April 10, 2018
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Tim Disher writes: I have been asked to run some regularized regressions on a small N high p situation, which for the primary outcome has lead to more realistic coefficient estimates and better performance on cv (yay!). Rstanarm made this process very easy for me so I am grateful for it. I have now been […] The post Fitting a hierarchical model without losing control appeared first on Statistical Modeling,…

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Learn by experimenting!

April 7, 2018
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A students wrote in one of his homework assignments: Sidenote: I know some people say you’re not supposed to use loops in R, but I’ve never been totally sure why this is (a speed thing?). My first computer language was Java, so my inclination is to think in loops before using some of the other […] The post Learn by experimenting! appeared first on Statistical Modeling, Causal Inference, and Social…

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Bayesian inference for A/B testing: Lauren Kennedy and I speak at the NYC Women in Machine Learning and Data Science meetup tomorrow (Tues 27 Mar) 7pm

March 26, 2018
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Here it is: Bayesian inference for A/B testing Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University Lauren Kennedy, Columbia Population Research Center, Columbia University Suppose we want to use empirical data to compare two or more decisions or treatment options. Classical statistical methods based on statistical significance and p-values break down […] The post Bayesian inference for A/B testing: Lauren Kennedy and I speak at the…

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