Posts Tagged ‘ Statistical computing ’

The network of models and Bayesian workflow

October 23, 2017
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This is important, it’s been something I’ve been thinking about for decades, it just came up in an email I wrote, and it’s refreshingly unrelated to recent topics of blog discussion, so I decided to just post it right now out of sequence (next slot on the queue is in May 2018). Right now, standard […] The post The network of models and Bayesian workflow appeared first on Statistical Modeling,…

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Workshop on Interpretable Machine Learning

October 11, 2017
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Andrew Gordon Wilson sends along this conference announcement: NIPS 2017 Symposium Interpretable Machine Learning Long Beach, California, USA December 7, 2017 Call for Papers: We invite researchers to submit their recent work on interpretable machine learning from a wide range of approaches, including (1) methods that are designed to be more interpretable from the start, […] The post Workshop on Interpretable Machine Learning appeared first on Statistical Modeling, Causal Inference,…

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Splines in Stan; Spatial Models in Stan !

October 10, 2017
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Splines in Stan; Spatial Models in Stan !

Two case studies: Splines in Stan, by Milad Kharratzadeh. Spatial Models in Stan: Intrinsic Auto-Regressive Models for Areal Data, by Mitzi Morris. This is great. Thanks, Mitzi! Thanks, Milad! The post Splines in Stan; Spatial Models in Stan ! appea...

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“5 minutes? Really?”

October 2, 2017
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Bob writes: Daniel says this issue https://github.com/stan-dev/stan/issues/795#issuecomment-26390557117 is an easy 5-minute fix. In my ongoing role as wet blanket, let’s be realistic. It’s sort of like saying it’s an hour from here to Detroit because that’s how long the plane’s in the air. Nothing is a 5 minute fix (door to door) for Stan and […] The post “5 minutes? Really?” appeared first on Statistical Modeling, Causal Inference, and Social…

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“From ‘What If?’ To ‘What Next?’ : Causal Inference and Machine Learning for Intelligent Decision Making”

October 2, 2017
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Panos Toulis writes in to announce this conference: NIPS 2017 Workshop on Causal Inference and Machine Learning (WhatIF2017) “From ‘What If?’ To ‘What Next?’ : Causal Inference and Machine Learning for Intelligent Decision Making” — December 8th 2017, Long Beach, USA. Submission deadline for abstracts and papers: October 31, 2017 Acceptance decisions: November 7, 2017 […] The post “From ‘What If?’ To ‘What Next?’ : Causal Inference and Machine Learning…

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Will Stanton hit 61 home runs this season?

September 21, 2017
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Will Stanton hit 61 home runs this season?

[edit: Juho Kokkala corrected my homework. Thanks! I updated the post. Also see some further elaboration in my reply to Andrew’s comment. As Andrew likes to say …] So far, Giancarlo Stanton has hit 56 home runs in 555 at bats over 149 games. Miami has 10 games left to play. What’s the chance he’ll […] The post Will Stanton hit 61 home runs this season? appeared first on Statistical…

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Call for papers: Probabilistic Programming Languages, Semantics, and Systems (PPS 2018)

September 20, 2017
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I’m on the program committee and they say they’re looking to broaden their horizons this year to include systems like Stan. The workshop is part of POPL, the big programming language theory conference. Here’s the official link PPS 2018 home page Call for extended abstracts (2 pages) The submissions are two-page extended abstracts and the […] The post Call for papers: Probabilistic Programming Languages, Semantics, and Systems (PPS 2018) appeared…

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The fundamental abstractions underlying BUGS and Stan as probabilistic programming languages

September 7, 2017
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Probabilistic programming languages I think of BUGS and Stan as probabilistic programming languages because their variables may be used to denote random variables, with function application doing the right thing in terms of propagating randomness (usually encoding uncertainty in a Bayesian setting). They are not probabilistic programming languages that provide an object language for inference; […] The post The fundamental abstractions underlying BUGS and Stan as probabilistic programming languages appeared…

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Iterative importance sampling

September 3, 2017
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Iterative importance sampling

Aki points us to some papers: Langevin Incremental Mixture Importance Sampling Parallel Adaptive Importance Sampling Iterative importance sampling algorithms for parameter estimation problems Next one is not iterative, but interesting in other way Black-box Importance Sampling Importance sampling is what you call it when you’d like to have draws of theta from some target distribution […] The post Iterative importance sampling appeared first on Statistical Modeling, Causal Inference, and Social…

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Stan Weekly Roundup, 25 August 2017

August 25, 2017
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Stan Weekly Roundup, 25 August 2017

This week, the entire Columbia portion of the Stan team is out of the office and we didn’t have an in-person/online meeting this Thursday. Mitzi and I are on vacation, and everyone else is either teaching, TA-ing, or attending the Stan course. Luckily for this report, there’s been some great activity out of the meeting […] The post Stan Weekly Roundup, 25 August 2017 appeared first on Statistical Modeling, Causal…

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