iiinova — where your digital self keeps evolving

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Sam Power @spmontecarlo.bsky.social · 17/05/2025

the (rather condensed by my standards) slides for my own talk are available here: github.com/sampower88/t...

github.com

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Simon Cauchemez @scauchemez.bsky.social · 23/06/2025

Just few days left to apply to one of these postdoc positions in my infectious disease modelling Unit at @pasteur.fr in Paris!

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Noah Greifer @noahgreifer.bsky.social · 04/06/2025

Starting to look like I might not be able to work at Harvard anymore due to recent funding cuts. If you know of any open statistical consulting positions that support remote work or are NYC-based, please reach out! 😅

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ArXiv Paperboy (Stat.ME+Econ.EM) @paperposterbot.bsky.social · 06/05/2025

link 📈🤖 Wasserstein complexity penalization priors: a new class of penalizing complexity priors (Bolin, Simas, Xiong) Penalizing complexity (PC) priors provide a principled framework for reducing model complexity by penalizing the Kullback--Leibler Divergence (KLD) between a ``simple'' base model

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Aki Vehtari @avehtari.bsky.social · 04/03/2025

New paper Säilynoja, Johnson, Martin, and Vehtari, "Recommendations for visual predictive checks in Bayesian workflow" teemusailynoja.github.io/visual-predi... (also arxiv.org/abs/2503.01509)

Abstract
Introduction
A key step in the Bayesian workflow for model building is the graphical assessment of model predictions, whether these are drawn from the prior or posterior predictive distribution. The goal of these assessments is to identify whether the model is a reasonable (and ideally accurate) representation of the domain knowledge and/or observed data. There are many commonly used visual predictive checks which can be misleading if their implicit assumptions do not match the reality. Thus, there is a need for more guidance for selecting, interpreting, and diagnosing appropriate visualizations. As a visual predictive check itself can be viewed as a model fit to data, assessing when this model fails to represent the data is important for drawing well-informed conclusions.

Demonstration
We present recommendations for appropriate visual predictive checks for observations that are: continuous, discrete, or a mixture of the two. We also discuss diagnostics to aid in the selection of visual methods. Specifically, in the detection of an incorrect assumption of continuously-distributed data: identifying when data is likely to be discrete or contain discrete components, detecting and estimating possible bounds in data, and a diagnostic of the goodness-of-fit to data for density plots made through kernel density estimates.

Conclusion
We offer recommendations and diagnostic tools to mitigate ad-hoc decision-making in visual predictive checks. These contributions aim to improve the robustness and interpretability of Bayesian model criticism practices.

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Reposted by Olivier Supplisson

arxiv.stat.ME @arxiv-stat-me.bsky.social · 27/02/2025

Stephen Jun Villejo, Sara Martino, Janine Illian, William Ryan, Finn Lindgren Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration arxiv.org/abs/2502.18962

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Nick Huntington-Klein @nickchk.com · 25/02/2025

After a long wait, the working paper for the Many-Economists Project: The Sources of Researcher Variation in Economics. We had 146 teams perform the same research three times, each time with less freedom. What source of freedom leads to different choices and results? papers.ssrn.com/sol3/papers....

papers.ssrn.com

The Sources of Researcher Variation in Economics

We use a rigorous three-stage many-analysts design to assess how different researcher decisions—specifically data cleaning, research design, and the interpretat

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Chris Wymant @chriswymant.bsky.social · 30/01/2025

Two postdoc positions to work on virus epi & evolution in response to vaccination, with both theoretical models + data analysis. Paris/Montpellier. With Sylvain Gandon, Sébastien Lion, François Blanquart, Katrina Lythgoe, & Troy Day emploi.cnrs.fr/Offres/CDD/U... emploi.cnrs.fr/Offres/CDD/U...

emploi.cnrs.fr

Portail Emploi CNRS - Offre d'emploi - Chercheur.e postdoctoral H/F en épidémiologie évolutive

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Olivier Supplisson @osupplisson.bsky.social · 28/01/2025

⚠️ Banger alert⚠️ "INLA: past, present, and future. A workshop in honour of Håvard Rue’s 60th birthday." Don't miss it: lnkd.in/dJDa3x_S When: 21-23 May 2025 Where: Glasgow So happy to be able to go there ✌ #StatsSky #Bayesian

lnkd.in

This link will take you to a page that’s not on LinkedIn

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Anne Cori @anne-cori.bsky.social · 27/01/2025

Our short course in infectious disease epidemiology and control is now open for applications! I am proud to be the director of this popular hands-on course which will teach you the basics of epidemic modelling in just two weeks! Apply here and spread the word! www.infectiousdiseasemodels.org

infectiousdiseasemodels.org

Epidemiology & Control of Infectious Diseases - Short Course

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Simon Cauchemez @scauchemez.bsky.social · 08/12/2024

If you’ve just arrived on BlueSky and are interested in infectious disease modelling, these starter packs are for you. 👇 I update them regularly, but I am sure I’ve missed many colleagues so don’t hesitate to send suggestions!

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Simon Cauchemez @scauchemez.bsky.social · 22/11/2024

Infectious Disease Modelling starter pack update! First pack is full so I created a second one. Pls keep on sending suggestions! (bio should contain experience relevant for this pack) IDModelling pack 1: go.bsky.app/86Ao1a5 IDModelling pack 2 : go.bsky.app/2oBB7KX

go.bsky.app

Infectious Disease Modelling #IDModelling

Join the conversation

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Marvin Schmitt @marvin-schmitt.com · 17/11/2024

I created a starter pack for simulation-based inference (aka. likelihood-free inference). Let me know if you’d like me to add you. go.bsky.app/GVnJRoK

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Richard Everitt @bayesianstats.bsky.social · 15/11/2024

I made a starter-pack for Statistics and Statistics-related groups, departments or organisations. Please share, and suggest accounts that I have missed. go.bsky.app/q6MfWL

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Dr Roz Eggo @rozeggo.bsky.social · 15/11/2024

Starter pack of infectious disease modellers from CMMID - the Centre for Mathematical Modelling of Infectious Diseases at LSHTM. We are 150 in CMMID but just getting started on Bluesky! go.bsky.app/625gwoG

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Richard Riley (R²) @richarddriley.bsky.social · 04/01/2024

Personal reflection: "Clinical prediction models & the multiverse of madness" Thanks to BMC Medicine for 'getting this' Many reviewers/Eds pushed for writing style & tone changes This thread delves into this & why we stuck to our original vision bmcmedicine.biomedcentral.com/articles/10.... 1/n

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