Posts Tagged ‘ Bayesian statistics ’

Come and work with us!

January 18, 2017
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Stan is an open-source, state-of-the-art probabilistic programming language with a high-performance Bayesian inference engine written in C++. Stan had been successfully applied to modeling problems with hundreds of thousands of parameters in fields as diverse as econometrics, sports analytics, physics, pharmacometrics, recommender systems, political science, and many more. Research using Stan has been featured in […] The post Come and work with us! appeared first on Statistical Modeling, Causal Inference,…

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Laurie Davies: time series decomposition of birthday data

January 17, 2017
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On the cover of BDA3 is a Bayesian decomposition of the time series of birthdays in the U.S. over a 20-year period. We modeled the data as a sum of Gaussian processes and fit it using GPstuff. Occasionally we fit this model to new data; see for example this discussion of Friday the 13th and […] The post Laurie Davies: time series decomposition of birthday data appeared first on Statistical…

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Stan is hiring! hiring! hiring! hiring!

January 17, 2017
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[insert picture of adorable cat entwined with Stan logo] We’re hiring postdocs to do Bayesian inference. We’re hiring programmers for Stan. We’re hiring a project manager. How many people we hire depends on what gets funded. But we’re hiring a few people for sure. We want the best best people who love to collaborate, who […] The post Stan is hiring! hiring! hiring! hiring! appeared first on Statistical Modeling, Causal…

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To know the past, one must first know the future: The relevance of decision-based thinking to statistical analysis

January 15, 2017
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We can break up any statistical problem into three steps: 1. Design and data collection. 2. Data analysis. 3. Decision making. It’s well known that step 1 typically requires some thought of steps 2 and 3: It is only when you have a sense of what you will do with your data, that you can […] The post To know the past, one must first know the future: The relevance…

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New year resolution

January 13, 2017
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New year resolution

Now that the Christmas break is just a distant memory (Marta would say that I am quite happy with that $-$ she thinks I'm like the Grinch around the Christmas holiday. And she is right), I've given way to my new year's resolution of finally, prope...

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“A Conceptual Introduction to Hamiltonian Monte Carlo”

January 12, 2017
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“A Conceptual Introduction to Hamiltonian Monte Carlo”

Michael Betancourt writes: Hamiltonian Monte Carlo has proven a remarkable empirical success, but only recently have we begun to develop a rigorous understanding of why it performs so well on difficult problems and how it is best applied in practice. Unfortunately, that understanding is con- fined within the mathematics of differential geometry which has limited […] The post “A Conceptual Introduction to Hamiltonian Monte Carlo” appeared first on Statistical Modeling,…

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I’ve said it before and I’ll say it again

January 10, 2017
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I’ve said it before and I’ll say it again

Ryan Giordano, Tamara Broderick, and Michael Jordan write: In Bayesian analysis, the posterior follows from the data and a choice of a prior and a likelihood. One hopes that the posterior is robust to reasonable variation in the choice of prior, since this choice is made by the modeler and is often somewhat subjective. A […] The post I’ve said it before and I’ll say it again appeared first on…

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Nooooooo, just make it stop, please!

January 5, 2017
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Nooooooo, just make it stop, please!

Dan Kahan wrote: You should do a blog on this. I replied: I don’t like this article but I don’t really see the point in blogging on it. Why bother? Kahan: BECAUSE YOU REALLY NEVER HAVE EXPLAINED WHY. Gelman-Rubin criticque of BIC is *not* responsive; you have something in mind—tell us what, pls! Inquiring minds […] The post Nooooooo, just make it stop, please! appeared first on Statistical Modeling, Causal…

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Steve Fienberg

December 20, 2016
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I did not know Steve Fienberg well, but I met him several times and encountered his work on various occasions, which makes sense considering his research area was statistical modeling as applied to social science. Fienberg’s most influential work must have been his books on the analysis of categorical data, work that was ahead of […] The post Steve Fienberg appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Movie stars

December 16, 2016
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Our search for potential alternatives to an academic career, in the face of increasing competition and difficulties in securing grant money has now led Jolene, Marcos and me to seek employment in the show-biz $-$ just in case we fail to recruit enough ...

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