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#bayesian

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tagesschau<p>Die schwierige Bergung der Luxusjacht "Bayesian"</p><p>Eine riesige Luxusjacht sinkt im Mittelmeer: Das Unglück der "Bayesian", bei dem sieben Menschen starben, sorgte 2024 für Schlagzeilen und Spekulationen. Nun soll das Wrack geborgen werden, doch die Aktion verzögert sich.</p><p>➡️ <a href="https://www.tagesschau.de/ausland/europa/bayesian-bergung-100.html?at_medium=mastodon&amp;at_campaign=tagesschau.de" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">tagesschau.de/ausland/europa/b</span><span class="invisible">ayesian-bergung-100.html?at_medium=mastodon&amp;at_campaign=tagesschau.de</span></a></p><p><a href="https://ard.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a></p>
Dr Mircea Zloteanu 🌼🐝<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statstab</span></a> #329 Bayesian versus frequentist approaches in multilevel single-case designs: on power and type I error rate</p><p>Thoughts: An interesting project highlighting some benefits of <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> methods for <a href="https://mastodon.social/tags/nof1" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>nof1</span></a> designs.</p><p><a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>stats</span></a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>r</span></a> <a href="https://mastodon.social/tags/sced" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>sced</span></a> <a href="https://mastodon.social/tags/mixedeffects" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mixedeffects</span></a></p><p><a href="https://osf.io/k7b82/files/osfstorage" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">osf.io/k7b82/files/osfstorage</span><span class="invisible"></span></a></p>
💧🌏 Greg Cocks<p>Observations Reveal Changing Coastal Storm Extremes Around The United States<br>--<br><a href="https://doi.org/10.1038/s41558-025-02315-z" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1038/s41558-025-023</span><span class="invisible">15-z</span></a> &lt;-- shared paper<br>--<br><a href="https://techhub.social/tags/GIS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GIS</span></a> <a href="https://techhub.social/tags/spatial" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatial</span></a> <a href="https://techhub.social/tags/mapping" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mapping</span></a> <a href="https://techhub.social/tags/extremeweather" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>extremeweather</span></a> <a href="https://techhub.social/tags/coast" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>coast</span></a> <a href="https://techhub.social/tags/coastal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>coastal</span></a> <a href="https://techhub.social/tags/spatialanalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatialanalysis</span></a> <a href="https://techhub.social/tags/spatiotemporal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatiotemporal</span></a> <a href="https://techhub.social/tags/model" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>model</span></a> <a href="https://techhub.social/tags/modeling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>modeling</span></a> <a href="https://techhub.social/tags/communities" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>communities</span></a> <a href="https://techhub.social/tags/publicsafety" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>publicsafety</span></a> <a href="https://techhub.social/tags/climatechange" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>climatechange</span></a> <a href="https://techhub.social/tags/stormsurge" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>stormsurge</span></a> <a href="https://techhub.social/tags/USA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>USA</span></a> <a href="https://techhub.social/tags/flood" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>flood</span></a> <a href="https://techhub.social/tags/flooding" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>flooding</span></a> <a href="https://techhub.social/tags/risk" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>risk</span></a> <a href="https://techhub.social/tags/hazard" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hazard</span></a> <a href="https://techhub.social/tags/damage" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>damage</span></a> <a href="https://techhub.social/tags/infrastructure" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>infrastructure</span></a> <a href="https://techhub.social/tags/cost" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>cost</span></a> <a href="https://techhub.social/tags/economics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>economics</span></a> <a href="https://techhub.social/tags/mitigation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mitigation</span></a> <a href="https://techhub.social/tags/insurance" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>insurance</span></a> <a href="https://techhub.social/tags/sealevel" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>sealevel</span></a> <a href="https://techhub.social/tags/SLR" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SLR</span></a> <a href="https://techhub.social/tags/sealevelrise" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>sealevelrise</span></a> <a href="https://techhub.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://techhub.social/tags/hierarchical" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hierarchical</span></a> <a href="https://techhub.social/tags/framework" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>framework</span></a> <a href="https://techhub.social/tags/tideguage" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tideguage</span></a> <a href="https://techhub.social/tags/tide" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tide</span></a> <a href="https://techhub.social/tags/tidal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tidal</span></a> <a href="https://techhub.social/tags/water" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>water</span></a> <a href="https://techhub.social/tags/hydrology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hydrology</span></a> <a href="https://techhub.social/tags/hydrography" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hydrography</span></a> <a href="https://techhub.social/tags/extremes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>extremes</span></a> <a href="https://techhub.social/tags/intensity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>intensity</span></a> <a href="https://techhub.social/tags/monitoring" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>monitoring</span></a></p>
pglpm<p><span class="h-card" translate="no"><a href="https://fosstodon.org/@Posit" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>Posit</span></a></span> </p><p>It's important to emphasize that "realistic-looking" data does *not* mean "realistic" data – especially high-dimensional data (unfortunately that post doesn't warn against this).</p><p>If one had an algorithm that generated realistic data for a given inference problem, it would mean that that inference problem had been solved. So: for educational purposes, why not. But for validation-like purposes, use with uttermost caution and at your own peril.</p><p><a href="https://c.im/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rstats</span></a> <a href="https://c.im/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a> <a href="https://c.im/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a></p>
Alex Holcombe<p>A <a href="https://fediscience.org/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> blogpost, by two of my undergraduate students! It's their report on their learning Bayesian modeling by applying it to my lab's data.<br><a href="https://alexholcombe.github.io/brms_psychometric_variableGuessRate_lapseRate/DenisonBlog.html" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">alexholcombe.github.io/brms_ps</span><span class="invisible">ychometric_variableGuessRate_lapseRate/DenisonBlog.html</span></a><br>Summary: we learned to use brms. But had trouble when we added more than one or two factors to the model. Little idea why; haven't had time to tinker much with that.</p>
Peter McMahan<p>I'm explaining Hamiltonian Monte Carlo in my grad-level stats class tomorrow, so I put together this animation illustrating HMC in one dimension. I find it very soothing.</p><p><a href="https://mas.to/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> <a href="https://mas.to/tags/BayesianInference" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BayesianInference</span></a> <a href="https://mas.to/tags/posterior" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>posterior</span></a> <a href="https://mas.to/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>stats</span></a> <a href="https://mas.to/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>r</span></a> <a href="https://mas.to/tags/rlang" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rlang</span></a> <a href="https://mas.to/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a> <a href="https://mas.to/tags/MCMC" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MCMC</span></a></p>
🐜🦅<p>Got the physical copies of my Cambridge element in the mail. A reminder that the whole book is free to download until the end of February: <a href="https://doi.org/10.1017/9781009210171" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.1017/9781009210171</span><span class="invisible"></span></a></p><p><a href="https://fediphilosophy.org/tags/probability" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>probability</span></a> <a href="https://fediphilosophy.org/tags/philosophyofscience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>philosophyofscience</span></a> <a href="https://fediphilosophy.org/tags/confirmation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>confirmation</span></a> <a href="https://fediphilosophy.org/tags/induction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>induction</span></a> <a href="https://fediphilosophy.org/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a></p>
EdinbR (R usergroup)<p>GO GO GO! We're live next week in 40 George Square, <a href="https://fosstodon.org/tags/Edinburgh" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Edinburgh</span></a> </p><p>Come and hear Isabella and Jordan talk about <a href="https://fosstodon.org/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://fosstodon.org/tags/Statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Statistics</span></a> in <a href="https://fosstodon.org/tags/RStats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RStats</span></a> </p><p>Details: <a href="http://edinbr.org/edinbr/2025/02/17/February-meeting.html" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">http://</span><span class="ellipsis">edinbr.org/edinbr/2025/02/17/F</span><span class="invisible">ebruary-meeting.html</span></a></p><p><a href="https://fosstodon.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataScience</span></a> <a href="https://fosstodon.org/tags/Scotland" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Scotland</span></a> <a href="https://fosstodon.org/tags/MeetUp" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MeetUp</span></a></p>
Angela Glansbury 🚽<p>what's your funniest accidental death of 2024 <a href="https://todon.nl/tags/2024Poll" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>2024Poll</span></a> <a href="https://todon.nl/tags/poll" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>poll</span></a> </p><p>Shipping tycoon <a href="https://todon.nl/tags/AngelaChao" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AngelaChao</span></a> drink driving her <a href="https://todon.nl/tags/Tesla" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Tesla</span></a> into a pond and drowning? 🌊 🚗 </p><p>Tech entrepreneur <a href="https://todon.nl/tags/MikeLynch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MikeLynch</span></a> being accidentally assassinated by <a href="https://todon.nl/tags/HP" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>HP</span></a> when his 56m yacht the <a href="https://todon.nl/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> sank off the coast of Sicily?🌊⛵ </p><p><a href="https://todon.nl/tags/BrianThompson" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BrianThompson</span></a> the late healthcare CEO who accidentally intercepted a mysterious bullet fired probably from a <a href="https://todon.nl/tags/Welrod" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Welrod</span></a> or <a href="https://todon.nl/tags/StationSIX9" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>StationSIX9</span></a> ⚰️🤔 </p><p>Billionaire founder of high street fashion chain <a href="https://todon.nl/tags/Mango" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mango</span></a> <a href="https://todon.nl/tags/IsakAndic" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>IsakAndic</span></a> who fell into a ravine🏔️🥴</p>
Daniel Lakeland<p>I got an email from the author promoting this benchmark comparison of <a href="https://mastodon.sdf.org/tags/Julialang" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Julialang</span></a> + StanBlocks + <a href="https://mastodon.sdf.org/tags/Enzyme" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Enzyme</span></a> vs <a href="https://mastodon.sdf.org/tags/Stan" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Stan</span></a> runtimes.</p><p>StanBlocks is a macro package for Julia that mimics the structure of a Stan program. This is the first I've heard about it.</p><p>A considerable number of these models are faster in Julia than Stan, maybe even most of them. </p><p><a href="https://nsiccha.github.io/StanBlocks.jl/performance.html" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">nsiccha.github.io/StanBlocks.j</span><span class="invisible">l/performance.html</span></a></p><p><a href="https://mastodon.sdf.org/tags/bayes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.sdf.org/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.sdf.org/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a></p>
Pierre-Simon Laplace<p>📢 Episode 120 is Live!</p><p><a href="https://learnbayesstats.com/episodes/8f372809-3905-4110-8e1b-2f5ca1f95b33" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">learnbayesstats.com/episodes/8</span><span class="invisible">f372809-3905-4110-8e1b-2f5ca1f95b33</span></a></p><p>🎙️ In this LBS episode, Alexandre Andorra, Liza Semenova, and Chris Wymant explore the intersection of epidemiology, Bayesian statistics, and data science!</p><p><a href="https://mstdn.science/tags/LearningBayesianStatistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LearningBayesianStatistics</span></a> <a href="https://mstdn.science/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a></p>
Nick Byrd, Ph.D.<p>A <a href="https://nerdculture.de/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a>, <a href="https://nerdculture.de/tags/DualProcessTheory" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DualProcessTheory</span></a> inspired, multinomial approach to moral dilemmas found the<br>- “do no harm” impulse predicted by class, but not reflection.<br>- “some harm for greater good” responses predicted by reflection, not class.</p><p><a href="https://doi.org/10.1007/s11186-024-09584-1" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1007/s11186-024-095</span><span class="invisible">84-1</span></a></p><p><a href="https://nerdculture.de/tags/xPhi" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>xPhi</span></a> <a href="https://nerdculture.de/tags/psycholoy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>psycholoy</span></a> <a href="https://nerdculture.de/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>stats</span></a></p>
Cheng Soon Ong<p>New book on Bayesian inference and human cognition. I have always enjoyed material from Tom Griffiths and also from Josh Tenenbaum, and I expect this new collected chapters would also be excellent. If you want to explore more literature, the contributing authors of individual chapters are also wonderful.</p><p><a href="https://mitpress.ublish.com/ebook/bayesian-models-of-cognition-reverse-engineering-the-mind-preview/12799/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">mitpress.ublish.com/ebook/baye</span><span class="invisible">sian-models-of-cognition-reverse-engineering-the-mind-preview/12799/</span></a></p><p><a href="https://masto.ai/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://masto.ai/tags/Cognition" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Cognition</span></a> <a href="https://masto.ai/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a></p>
pglpm<p><span class="h-card" translate="no"><a href="https://lgbtqia.space/@AeonCypher" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>AeonCypher</span></a></span> <span class="h-card" translate="no"><a href="https://mastodon.world/@paninid" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>paninid</span></a></span> </p><p>"A p-value is an <a href="https://c.im/tags/estimate" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>estimate</span></a> of p(Data | Null Hypothesis). " – not correct. A p-value is an estimate of</p><p>p(Data or other imagined data | Null Hypothesis)</p><p>so not even just of the actual data you have. Which is why p-values depend on your stopping rule (and do not satisfy the "likelihood principle"). In this regard, see Jeffreys's quote below.</p><p>Imagine you design an experiment this way: "I'll test 10 subjects, and in the meantime I apply for a grant. At the time the 10th subject is tested, I'll know my application's outcome. If the outcome is positive, I'll test 10 more subjects; if it isn't, I'll stop". Not an unrealistic situation.</p><p>With this stopping rule, your p-value will depend on the probability that you get the grant. This is not a joke.</p><p>"*What the use of P implies, therefore, is that a hypothesis that may be true may be rejected because it has not predicted observable results that have not occurred.* This seems a remarkable procedure. On the face of it the fact that such results have not occurred might more reasonably be taken as evidence for the law, not against it." – H. Jeffreys, "Theory of Probability" §&nbsp;VII.7.2 (emphasis in the original) &lt;<a href="https://doi.org/10.1093/oso/9780198503682.001.0001" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1093/oso/9780198503</span><span class="invisible">682.001.0001</span></a>&gt;.</p><p><a href="https://c.im/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> <a href="https://c.im/tags/bayes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayes</span></a> <a href="https://c.im/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a></p>
➴➴➴Æ🜔Ɲ.Ƈꭚ⍴𝔥єɼ👩🏻‍💻<p><span class="h-card" translate="no"><a href="https://mastodon.world/@paninid" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>paninid</span></a></span> p-values, to a large extent, exist because calculating the posterior is computationally expensive. Not all fields use the .05 cutoff.</p><p>A p-value is an <a href="https://lgbtqia.space/tags/estimate" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>estimate</span></a> of p(Data | Null Hypothesis). If the two <a href="https://lgbtqia.space/tags/hypotheses" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hypotheses</span></a> are equally likely and they are mutually exclusive and they are closed over the <a href="https://lgbtqia.space/tags/hypothesis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hypothesis</span></a> space, then this is the same as p(Hypothesis | Data).</p><p>Meaning, under certain assumption, the p-value does represent the actually probability of being wrong. </p><p>However, given modern computers, there is no reason that <a href="https://lgbtqia.space/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> odds-ratios can't completely replace their usage and avoid the many many problems with p-values.</p>
Lace Padilla<p>Do you use Probability Density Function (PDF) plots to show your results? <br>Discover how compressing PDFs impacts data interpretation in research! </p><p>Racquel Fygenson reveals surprising insights from our study on plot scaling. 📈 <br>Video: <a href="https://www.youtube.com/watch?v=BEsD1RIIjCo&amp;ab_channel=Dr.LacePadilla" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">youtube.com/watch?v=BEsD1RIIjC</span><span class="invisible">o&amp;ab_channel=Dr.LacePadilla</span></a> <br>Paper: <a href="https://vis.khoury.northeastern.edu/pubs/Fygenson2024ImpactVerticalScaling/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">vis.khoury.northeastern.edu/pu</span><span class="invisible">bs/Fygenson2024ImpactVerticalScaling/</span></a></p><p><a href="https://vis.social/tags/Datavisualization" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Datavisualization</span></a> <a href="https://vis.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a></p>
Tomasz Woźniak<p>Hey! Please have a look at my lecture slides on 𝘉𝘢𝘺𝘦𝘴𝘪𝘢𝘯 𝘝𝘦𝘤𝘵𝘰𝘳 𝘈𝘶𝘵𝘰𝘳𝘦𝘨𝘳𝘦𝘴𝘴𝘪𝘰𝘯𝘴 with a forecasting application of the material implemented using my 𝗥 package 𝗯𝘀𝘃𝗮𝗿𝗦𝗜𝗚𝗡𝘀! 💙🖤 </p><p><a href="https://bsvars.github.io/2024-10-be24-bsvarSIGNs" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">bsvars.github.io/2024-10-be24-</span><span class="invisible">bsvarSIGNs</span></a></p><p>No sign restrictions are involved here! Just the VAR model with hierarchical prior and Bayesian forecasting. Juicy! 🍭🍬 </p><p><a href="https://fosstodon.org/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://fosstodon.org/tags/VARs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>VARs</span></a> <a href="https://fosstodon.org/tags/forecasting" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>forecasting</span></a> <a href="https://fosstodon.org/tags/bsvarSIGNs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bsvarSIGNs</span></a> <a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rstats</span></a></p>
Aki Vehtari<p>The latest `brms` CRAN release added support for `priorsense` for easy prior and likelihood sensitivity analysis <a href="https://doi.org/10.1007/s11222-023-10366-5" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1007/s11222-023-103</span><span class="invisible">66-5</span></a></p><p>```<br>&gt; fit |&gt;<br> powerscale_plot_dens(variable='b_doseg', help_text=FALSE) +<br> labs(x='Dose (g) coefficient', y=NULL) <br>&gt; powerscale_sensitivity(fit, variable='b_doseg')<br>Sensitivity based on cjs_dist:<br> variable prior likelihood diagnosis <br> b_doseg 0.236 0.219 prior-data conflict<br>```</p><p><a href="https://bayes.club/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://bayes.club/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rstats</span></a></p>
F. Javier Rubio<p>If you are interested in pursuing a <a href="https://mastodon.social/tags/PhD" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PhD</span></a> at <span class="h-card" translate="no"><a href="https://mastodon.social/@statistics_UCL" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>statistics_UCL</span></a></span> (Oct/25) in <a href="https://mastodon.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> methodology and computational <a href="https://mastodon.social/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a>, co-supervised by Sam Livingstone and myself, feel free to reach out. A strong academic background and proven experience in these areas are essential.</p>
Frederic Blum<p>New article published: <a href="https://doi.org/10.1038/s41562-024-01988-4" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1038/s41562-024-019</span><span class="invisible">88-4</span></a></p><p>We have found that over 51 diverse languages, word-initial consonants are systematically longer than their counterparts in other positions.</p><p>While the study only analyzes observational data, we think this might be one of several cues for segmenting the acoustic stream into words - present in possibly most of the world's languages.</p><p><a href="https://social.mpdl.mpg.de/tags/linguistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>linguistics</span></a> <a href="https://social.mpdl.mpg.de/tags/WEIRD" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>WEIRD</span></a> <a href="https://social.mpdl.mpg.de/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://social.mpdl.mpg.de/tags/typology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>typology</span></a></p>
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