Author: Aki Vehtari

StanCon 2018 Helsinki talk slides, notebooks and code online

StanCon 2018 Helsinki talk slides, notebooks and code have been sometime available in StanCon talks repository, but it seems we forgot to announce this. The StanCon 2018 Helsinki talk list includes also links to videos. StanCon’s version of conference proceedings is a collection of contributed talks based on interactive notebooks. Every submission is peer reviewed […]

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Postdocs and Research fellows for combining probabilistic programming, simulators and interactive AI

Here’s a great opportunity for those interested in probabilistic programming and workflows for Bayesian data analysis: We (including me, Aki) are looking for outstanding postdoctoral researchers and research fellows to work for a new exciting project in the crossroads of probabilistic programming, simulator-based inference and user interfaces. You will have an opportunity to work with […]

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Postdoc position: Stan and composite mechanistic and data-driven models of cellular metabolism

Very cool project and possibility to work 3 years developing Stan and collaborating with me (Aki) and other Stan development team. Deadline for applications is 22 October. Quantitative Modelling of Cell Metabolism (QMCM) group headed by Professor Lars Keld Nielsen at DTU, Copenhagen, is looking for experienced Bayesian statistician for a postdoc position. Group specializes […]

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StanCon 2018 Helsinki tutorial videos online

StanCon 2018 Helsinki tutorial videos are now online at Stan YouTube channel List of tutorials at StanCon 2018 Helsinki Basics of Bayesian inference and Stan, parts 1 + 2, Jonah Gabry & Lauren Kennedy Hierarchical models, parts 1 + 2, Ben Goodrich Stan C++ development: Adding a new function to Stan, parts 1 + 2, […]

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When LOO and other cross-validation approaches are valid

Introduction Zacco asked in Stan discourse whether LOO is valid for phylogenetic models. He also referred to Dan’s excellent blog post which mentioned iid assumption. Instead of iid it would be better to talk about exchangeability assumption, but I (Aki) got a bit lost in my discourse answer (so don’t bother to go read it). […]

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When LOO and other cross-validation approaches are valid

Introduction Zacco asked in Stan discourse whether leave-one-out (LOO) cross-validation is valid for phylogenetic models. He also referred to Dan’s excellent blog post which mentioned iid assumption. Instead of iid it would be better to talk about exchangeability assumption, but I (Aki) got a bit lost in my discourse answer (so don’t bother to go […]

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Parsimonious principle vs integration over all uncertainties

tl;dr If you have bad models, bad priors or bad inference choose the simplest possible model. If you have good models, good priors, good inference, use the most elaborate model for predictions. To make interpretation easier you may use a smaller model with similar predictive performance as the most elaborate model. Merijn Mestdagh emailed me […]

The post Parsimonious principle vs integration over all uncertainties appeared first on Statistical Modeling, Causal Inference, and Social Science.

Parsimonious principle vs integration over all uncertainties

tl;dr If you have bad models, bad priors or bad inference choose the simplest possible model. If you have good models, good priors, good inference, use the most elaborate model for predictions. To make interpretation easier you may use a smaller model with similar predictive performance as the most elaborate model. Merijn Mestdagh emailed me […]

The post Parsimonious principle vs integration over all uncertainties appeared first on Statistical Modeling, Causal Inference, and Social Science.