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#bayes

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Pierre-Simon Laplace<p>Models need more than pattern-matching.<br>They need causal understanding.</p><p>In this episode, Robert Ness joins Alex Andorra to explore:</p><p>⚡ Why models need real-world biases<br>🧠 How causal rep learning is reshaping AI<br>🤖 What it takes to add causality to DL</p><p>🎧<a href="https://www.learnbayesstats.com/episode/137-causal-ai-generative-models-robert-ness" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">learnbayesstats.com/episode/13</span><span class="invisible">7-causal-ai-generative-models-robert-ness</span></a></p><p><a href="https://mstdn.science/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mstdn.science/tags/podcast" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>podcast</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #386 {bayestestR} Evaluating Evidence and Making Decisions using Bayesian Statistics by <span class="h-card" translate="no"><a href="https://scicomm.xyz/@mattansb" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>mattansb</span></a></span> </p><p>Thoughts: Want to start using Bayesian stats? Here is a quick but comprehensive guide in <a href="https://mastodon.social/tags/R" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>R</span></a></p><p><a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/mcmc" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mcmc</span></a> <a href="https://mastodon.social/tags/easystats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>easystats</span></a> <a href="https://mastodon.social/tags/guide" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>guide</span></a></p><p><a href="https://mattansb.github.io/bayesian-evidence/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">mattansb.github.io/bayesian-ev</span><span class="invisible">idence/</span></a></p>
Harishjosev<p>My latest post - On Probability…</p><p>Probability tracks change in knowledge, not a change in the event itself.</p><p><a href="https://fosstodon.org/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a> <a href="https://fosstodon.org/tags/epistemology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>epistemology</span></a> </p><p><a href="https://harishsnotebook.wordpress.com/2025/07/03/on-probability/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">harishsnotebook.wordpress.com/</span><span class="invisible">2025/07/03/on-probability/</span></a></p>
pglpm<p>Interested in trying out *Bayesian nonparametrics* for your statistical research?</p><p>I'd be very grateful if people tried out this R package for Bayesian nonparametric population inference, called "inferno" :</p><p>&lt;<a href="https://pglpm.github.io/inferno/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">pglpm.github.io/inferno/</span><span class="invisible"></span></a>&gt;</p><p>It is especially addressed to clinical and medical researchers, and allows for thorough statistical studies of subpopulations or subgroups.</p><p>Installation instructions are here: &lt;<a href="https://pglpm.github.io/inferno/index.html#installation" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">pglpm.github.io/inferno/index.</span><span class="invisible">html#installation</span></a>&gt;.</p><p>A step-by-step tutorial, guiding you through an example analysis of a simple dataset, is here: &lt;<a href="https://pglpm.github.io/inferno/articles/vignette_start.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">pglpm.github.io/inferno/articl</span><span class="invisible">es/vignette_start.html</span></a>&gt;.</p><p>The package has already been tested and used in concrete research about Alzheimer's Disease, Parkinson's Disease, drug discovery, and applications to machine learning.</p><p>Feedback is very welcome. If you find the package useful, feel free to advertise it a little :)</p><p><a href="https://c.im/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://c.im/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://c.im/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://c.im/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://c.im/tags/medicine" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>medicine</span></a> <a href="https://c.im/tags/datascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datascience</span></a></p>
Oliver D. Reithmaier<p>Off to <a href="https://infosec.exchange/tags/Verona" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Verona</span></a> to learn some more <a href="https://infosec.exchange/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a>! Will be there next week, so if any of you are as well and fancy a chat, let me know!</p>
Teresita Porter 🙋🏻‍♀️<p>eDNAjoint: An R package for interpreting paired or semi-paired environmental DNA and traditional survey data in a Bayesian framework</p><p><a href="https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.70000" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">besjournals.onlinelibrary.wile</span><span class="invisible">y.com/doi/full/10.1111/2041-210X.70000</span></a></p><p><a href="https://ecoevo.social/tags/eDNA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>eDNA</span></a> <a href="https://ecoevo.social/tags/environmentalDNA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>environmentalDNA</span></a> <a href="https://ecoevo.social/tags/Rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Rstats</span></a> <a href="https://ecoevo.social/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a></p>
Ross Gaylermaths/Bayes/probability/optimisation/inference questions
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #295 The Fallacy of the Null-Hypothesis Significance Test</p><p>Thoughts: "the [..] aim of a scientific experiment is not to precipitate decisions, but to make an appropriate adjustment in the degree to which one accepts, or believes, the hypothesis"</p><p><a href="https://mastodon.social/tags/NHST" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NHST</span></a> <a href="https://mastodon.social/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a> <a href="https://mastodon.social/tags/ConfidenceIntervals" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ConfidenceIntervals</span></a> <a href="https://mastodon.social/tags/pvalues" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pvalues</span></a> <a href="https://mastodon.social/tags/significance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>significance</span></a> <a href="https://mastodon.social/tags/testing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>testing</span></a> <a href="https://mastodon.social/tags/hypotheses" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>hypotheses</span></a> <a href="https://mastodon.social/tags/likelihood" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>likelihood</span></a> <a href="https://mastodon.social/tags/critique" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>critique</span></a> <a href="https://mastodon.social/tags/fallacy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fallacy</span></a></p><p><a href="http://stats.org.uk/statistical-inference/Rozeboom1960.pdf" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="ellipsis">stats.org.uk/statistical-infer</span><span class="invisible">ence/Rozeboom1960.pdf</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #293 The Bayesian Bootstrap</p><p>Thoughts: I need to think more on where bootstrapping makes sense in a bayesian setting. But here's a tutorial.</p><p><a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/bootstrap" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bootstrap</span></a> <a href="https://mastodon.social/tags/resampling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>resampling</span></a> </p><p><a href="https://towardsdatascience.com/the-bayesian-bootstrap-6ca4a1d45148/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">towardsdatascience.com/the-bay</span><span class="invisible">esian-bootstrap-6ca4a1d45148/</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #279 Diagnosing the Misuse of the Bayes Factor in Applied Research</p><p>Thoughts: As with NHST, Null Hypothesis Bayesian Testing (NHBT) can also be easily misunderstood.</p><p><a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.social/tags/NHBT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NHBT</span></a> <a href="https://mastodon.social/tags/misuse" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>misuse</span></a> <a href="https://mastodon.social/tags/QRPs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>QRPs</span></a> <a href="https://mastodon.social/tags/error" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>error</span></a></p><p><a href="https://journals.sagepub.com/doi/10.1177/25152459231213371" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">journals.sagepub.com/doi/10.11</span><span class="invisible">77/25152459231213371</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a> help: is there any online tutorial for ordinal CFA with {blavaan}?</p><p><a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.social/tags/blavaan" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>blavaan</span></a> <a href="https://mastodon.social/tags/lavaan" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lavaan</span></a> <a href="https://mastodon.social/tags/cfa" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cfa</span></a> <a href="https://mastodon.social/tags/sem" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sem</span></a> <a href="https://mastodon.social/tags/tutorial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tutorial</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #272 Different meanings of p-values</p><p>Thoughts: A riveting (&amp; confusing) discussion on the definitions &amp; properties of p-values. W/ guest appearance from some big names in stats, from all camps.</p><p><a href="https://mastodon.social/tags/NHST" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NHST</span></a> <a href="https://mastodon.social/tags/pvalues" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pvalues</span></a> <a href="https://mastodon.social/tags/divergence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>divergence</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/compatibility" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>compatibility</span></a></p><p><a href="https://statmodeling.stat.columbia.edu/2023/04/14/4-different-meanings-of-p-value-and-how-my-thinking-has-changed/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">statmodeling.stat.columbia.edu</span><span class="invisible">/2023/04/14/4-different-meanings-of-p-value-and-how-my-thinking-has-changed/</span></a></p>
pglpm<p><span class="h-card" translate="no"><a href="https://mastodon.social/@bthalpin" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>bthalpin</span></a></span> <br>Curiosity: what does it do if you ask for an 89% *credibility* interval, maybe even asking not to make distributional assumptions?</p><p><a href="https://c.im/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://c.im/tags/deepseek" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deepseek</span></a> <a href="https://c.im/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a></p>
Chad Scherrer<p>We'd like to benchmark our <a href="https://bsky.brid.gy/hashtag/rust" rel="nofollow noopener" target="_blank">#rust</a> DPMM sampler against some alternatives. What's the fastest you know of? <a href="https://bsky.brid.gy/hashtag/nonparametric" rel="nofollow noopener" target="_blank">#nonparametric</a> <a href="https://bsky.brid.gy/hashtag/bayes" rel="nofollow noopener" target="_blank">#bayes</a> <a href="https://bsky.brid.gy/hashtag/MCMC" rel="nofollow noopener" target="_blank">#MCMC</a></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" target="_blank">#<span>Julialang</span></a> + StanBlocks + <a href="https://mastodon.sdf.org/tags/Enzyme" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Enzyme</span></a> vs <a href="https://mastodon.sdf.org/tags/Stan" class="mention hashtag" rel="nofollow noopener" 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" 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" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.sdf.org/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.sdf.org/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #232 Bayesian Interval-Null Testing</p><p>Thoughts: @JASPStats has a module for Equivalence Tests that include Bayesian Overlapping and Non-Overlapping Hypothesis Testing.</p><p><a href="https://mastodon.social/tags/equivalencetests" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>equivalencetests</span></a> <a href="https://mastodon.social/tags/bayesfactors" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesfactors</span></a> <a href="https://mastodon.social/tags/jasp" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>jasp</span></a> <a href="https://mastodon.social/tags/noeffect" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>noeffect</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a><br> <a href="https://jasp-stats.org/2020/06/02/frequentist-and-bayesian-equivalence-testing-in-jasp/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">jasp-stats.org/2020/06/02/freq</span><span class="invisible">uentist-and-bayesian-equivalence-testing-in-jasp/</span></a></p>
Ulrike Hahn<p>„calling something logic doesn’t make it so. Calling someone rational doesn’t make it so“ </p><p>I’ve been thinking for a while that, as someone who works on human rationality and rational argument, I should write a blog post on what that actually means (and, maybe more importantly, doesn‘t mean).</p><p>in the meantime, though, I found much to agree with in this piece: </p><p>Title: The magical thinking of guys who love logic <br><a href="https://theoutline.com/post/7083/the-magical-thinking-of-guys-who-love-logic" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">theoutline.com/post/7083/the-m</span><span class="invisible">agical-thinking-of-guys-who-love-logic</span></a> </p><p><a href="https://fediscience.org/tags/logic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>logic</span></a> <a href="https://fediscience.org/tags/rationality" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rationality</span></a> <a href="https://fediscience.org/tags/argument" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>argument</span></a> <a href="https://fediscience.org/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #229 Prior Modeling<br>by <span class="h-card" translate="no"><a href="https://fediscience.org/@betanalpha" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>betanalpha</span></a></span> </p><p>Thoughts: Thorough overview of the prior elicitation process and ways to think about priors.</p><p><a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a> <a href="https://mastodon.social/tags/priors" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>priors</span></a> <a href="https://mastodon.social/tags/probability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>probability</span></a> <a href="https://mastodon.social/tags/metascience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>metascience</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a></p><p><a href="https://betanalpha.github.io/assets/case_studies/prior_modeling.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">betanalpha.github.io/assets/ca</span><span class="invisible">se_studies/prior_modeling.html</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #228 Applied Modelling in Drug Development - Setting priors in {brms}</p><p>Thoughts: Part of a larger book, useful bit for understanding how to set priors &amp; check them for bayesian models &amp; meta-analyses</p><p><a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a> <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>brms</span></a> <a href="https://mastodon.social/tags/priors" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>priors</span></a> <a href="https://mastodon.social/tags/metaanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>metaanalysis</span></a> <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>r</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/drugs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drugs</span></a> <a href="https://mastodon.social/tags/clinicaltrials" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>clinicaltrials</span></a> </p><p><a href="https://opensource.nibr.com/bamdd/src/01c_priors.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">opensource.nibr.com/bamdd/src/</span><span class="invisible">01c_priors.html</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #227 Parameterization of Response Distributions in {brms}</p><p>Thoughts: If you use <a href="https://mastodon.social/tags/brms" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>brms</span></a> and can read mathematical notation (who can't, right?), this page will be useful.</p><p><a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>r</span></a> <a href="https://mastodon.social/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> <a href="https://mastodon.social/tags/models" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>models</span></a> <a href="https://mastodon.social/tags/distributions" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>distributions</span></a> <a href="https://mastodon.social/tags/likelihood" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>likelihood</span></a> <a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a></p><p><a href="https://cran.r-project.org/web/packages/brms/vignettes/brms_families.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">cran.r-project.org/web/package</span><span class="invisible">s/brms/vignettes/brms_families.html</span></a></p>
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