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#bayes

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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>
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>
pglpm<p><span class="h-card" translate="no"><a href="https://lgbtqia.space/@AeonCypher" class="u-url mention" rel="nofollow noopener" 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" 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" 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" 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" 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></p>
moses<p>Part of a "Justification for Training" document that I'm working on. The job description is largely based on a current posting on Apple's jobs listing site titled "Applied Research Scientist, Health AI". <a href="https://jobs.apple.com/en-us/details/200428564/aiml-applied-research-scientist-health-ai" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">jobs.apple.com/en-us/details/2</span><span class="invisible">00428564/aiml-applied-research-scientist-health-ai</span></a></p><p><a href="https://mastodon.sdf.org/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://mastodon.sdf.org/tags/DataVisualisation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataVisualisation</span></a> <a href="https://mastodon.sdf.org/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://mastodon.sdf.org/tags/engineering" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>engineering</span></a> <a href="https://mastodon.sdf.org/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://mastodon.sdf.org/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.sdf.org/tags/experiments" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>experiments</span></a> <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/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://mastodon.sdf.org/tags/gdpr" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gdpr</span></a> <a href="https://mastodon.sdf.org/tags/career" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>career</span></a> <a href="https://mastodon.sdf.org/tags/training" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>training</span></a> <a href="https://mastodon.sdf.org/tags/Colorado" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Colorado</span></a></p>
Daniel Lakeland<p><a href="https://mastodon.sdf.org/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a> when the database crashed I lost some followers, but because I hadn't backed up my account yet, I am not sure who they all are. As an extended introduction I'll tag some common topics I like to discuss, maybe people will see those.<br><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> <a href="https://mastodon.sdf.org/tags/appliedmathematics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>appliedmathematics</span></a> <a href="https://mastodon.sdf.org/tags/ipv6" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ipv6</span></a> <a href="https://mastodon.sdf.org/tags/bufferbloat" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bufferbloat</span></a> <a href="https://mastodon.sdf.org/tags/quarto" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>quarto</span></a> <a href="https://mastodon.sdf.org/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://mastodon.sdf.org/tags/agentbasedmodels" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>agentbasedmodels</span></a> <a href="https://mastodon.sdf.org/tags/julialang" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>julialang</span></a> <a href="https://mastodon.sdf.org/tags/economics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>economics</span></a> <a href="https://mastodon.sdf.org/tags/biology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>biology</span></a> <a href="https://mastodon.sdf.org/tags/molecularbiology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>molecularbiology</span></a> <a href="https://mastodon.sdf.org/tags/ecology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ecology</span></a> <a href="https://mastodon.sdf.org/tags/forensics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>forensics</span></a> <a href="https://mastodon.sdf.org/tags/engineering" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>engineering</span></a></p>
George Ho<p>Since I’ve moved instances, I guess it’s time for another <a href="https://bright.rosy-colored.space/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a>!</p><p>I’m a <a href="https://bright.rosy-colored.space/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> scientist and <a href="https://bright.rosy-colored.space/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> engineer based in <a href="https://bright.rosy-colored.space/tags/NYC" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NYC</span></a>. I don’t really like making my employer part of my identity, but I currently work at Flatiron Health, and I was previously a quantitative finance researcher at a hedge fund. My career has brought me into communities for <a href="https://bright.rosy-colored.space/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a>, <a href="https://bright.rosy-colored.space/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> and <a href="https://bright.rosy-colored.space/tags/NLP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NLP</span></a>, where I usually go by Eigenfoo 🧑‍💻📚</p>
Stephen VaiseyI never really did it so here's my introduction.
Ed Merkle<p>New case study exploring likelihood computations (+ approximations) for Bayesian structural equation models with ordinal data, with application to WAIC and friends.</p><p><a href="https://ecmerkle.github.io/cs/ord_ic.html" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ecmerkle.github.io/cs/ord_ic.h</span><span class="invisible">tml</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/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a> <a href="https://mastodon.sdf.org/tags/mcmc" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mcmc</span></a> <a href="https://mastodon.sdf.org/tags/stan" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stan</span></a> <a href="https://mastodon.sdf.org/tags/sem" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sem</span></a></p>
Emtiyaz Khan<p>Who am I, and why am I here? <a href="https://mastodon.social/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a></p><p>I am a machine learning researcher, using tools from <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/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a>, <a href="https://mastodon.social/tags/optimization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>optimization</span></a>, <a href="https://mastodon.social/tags/informationgeometry" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>informationgeometry</span></a>, <a href="https://mastodon.social/tags/deeplearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deeplearning</span></a>, signal processing, etc.</p><p>I care deeply about people, their well-being, inclusion, diversity, equity, privacy, and justice.</p><p>I believe in slow and rigorous scientific process, to add value to existing knowledge, and improve positive impact on society.</p><p>I am here to learn about all of these.</p><p>More about at <a href="https://emtiyaz.github.io/" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">emtiyaz.github.io/</span><span class="invisible"></span></a></p>
Vanessa Brown<p><a href="https://fediscience.org/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a> Hi all!</p><p>I'm a clinical <a href="https://fediscience.org/tags/psychologist" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychologist</span></a>, cognitive <a href="https://fediscience.org/tags/neuroscientist" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuroscientist</span></a>, &amp; <a href="https://fediscience.org/tags/computational" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computational</span></a> modeler. I use <a href="https://fediscience.org/tags/reinforcementLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>reinforcementLearning</span></a> to understand how learning from rewards and punishments goes awry in <a href="https://fediscience.org/tags/anxiety" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>anxiety</span></a> <a href="https://fediscience.org/tags/trauma" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>trauma</span></a> and <a href="https://fediscience.org/tags/depression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>depression</span></a> to improve how <a href="https://fediscience.org/tags/psychotherapy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychotherapy</span></a> (esp CBT) and other treatments work. I also work on how to measure <a href="https://fediscience.org/tags/behavior" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>behavior</span></a> better using <a href="https://fediscience.org/tags/computationalModeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computationalModeling</span></a> (esp with <a href="https://fediscience.org/tags/bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayes</span></a> &amp; <a href="https://fediscience.org/tags/stan" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stan</span></a>), and how science can benefit communities typically marginalized in medical research.</p>
Martin Burgess<p><a href="https://fosstodon.org/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a> </p><p>Hi all, I'm a data scientist leading data at <a href="https://raisely.com" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">raisely.com</span><span class="invisible"></span></a> (an online fundraising platform). In my spare time I forecast Australian elections (<a href="https://buckleysandnone.com" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">buckleysandnone.com</span><span class="invisible"></span></a>) and do some research (gambling harms, COVID-19 vaccines etc 😅 ). </p><p>I'm keen on all things <a href="https://fosstodon.org/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a>, <a href="https://fosstodon.org/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a>, <a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rstats</span></a>, <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/stan" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stan</span></a>, <a href="https://fosstodon.org/tags/quarto" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>quarto</span></a> </p><p>Excited to meet you all!</p>
Daniel Heck<p>Hi! I am an associate professor of Psychological Methods at Philipps-Universität Marburg. </p><p>My <a href="https://mastodon.social/tags/research" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>research</span></a> focuses on cognitive and multinomial modeling, Bayesian statistics, <a href="https://mastodon.social/tags/Bayes" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bayes</span></a> factors, hierarchical models, meta-analysis, and <a href="https://mastodon.social/tags/psychometrics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>psychometrics</span></a>.</p><p>My personal website is: <a href="https://www.dwheck.de" rel="nofollow noopener" target="_blank"><span class="invisible">https://www.</span><span class="">dwheck.de</span><span class="invisible"></span></a></p>