Top Tweets for #Bayesian
#SFMMO #Validation Time!
π― 498 match calls across Europe's Top 5 leagues so far this season.
We are up from last week, but still trailing the market's closing odds:
β½οΈ SFMMO --- 54.0%
π Market --- 56.4%
#bayesian #Prediction #odds #FPL #Statistics
Graphical-SUBHO, is now live on github. Regress each genes on all the others under a horseshoe prior and rank the predictors by size of their coefficient. An edge enters the network only when both genes select each other.
https://t.co/ZfycDS7Uer
#network #bayesian #sparsedata
Im interested in what #bayesian statisticians make of this. Is "sure" meaningfully different from beyond reasonable doubt in probability terms, and would an explicit bayesian framing actually help (or hinder) lay juries?
Colloquially they are not synonymous in a statistical world
They equate to the
βSureβ maybe 95th percentile which is not good enough evidence because of many false positives
BARD would therefore be more like 99th%ile plus - in fact an explicitly Bayesian approach would be better and something that could be explained to waiting juries
If ppl are not smart enough to understand we have our test of if should be on a jury
Premier League #GW10 --- #cleansheets projections:
Contentious calls?
- Everton sneaking in at 2nd place ?! --- but the uncertainty says it all
- ManU more likely against Villa than City against Nottingham ?! --- home advantage kicking in
#bayesian #prediction #fpl #EPL
Fitting the same model hundreds of times? With MCMC, the cost scales with every fit.
Amortized Bayesian inference trains a network once on simulations, then returns posteriors in a single forward pass.
Read the full blog: https://t.co/6htPyyPZVW
#Bayesian #DataScience
A new store can forecast well and still add little if its sales mostly come from nearby Wegmans stores.
Our model forecasts the network with and without the site, so each neighbor gets its own expected sales change. Case study: https://t.co/UC5onh3zeN
#SiteSelection #Bayesian
Check out the latest article by our @LaStatale postdoc @FrancescoRenz27 published in @JASSSJournal where he presents a #Bayesian framework for a fast and systematic assessment of #parameter #identifiability of #ABM agent-based modeling! https://t.co/le3QHlpS4B
Excited to teach two virtual short courses with @Physacourses this November:
π
2β6 Nov: Causal AI Methods for Computational Biology
https://t.co/HXbP6E5Zcp
π
30 Nov β 4 Dec: Bayesian Methods for Biomedical Data Science
https://t.co/mmMPrSwX9D
#Bayesian #Causal #DataScience
Two sites can have equal expected sales and very different risk. The site-selection model we built with Wegmans gives each candidate a full distribution: the odds it clears its sales target and the expected hit to every nearby store.
Case study: https://t.co/s1SkOuFWRU
#Bayesian
Books teach you #Bayesian models but skip the practical parts: picking priors, checking your sampler, fixing a misbehaving model.
Lead instructor Chris Fonnesbeck explains how our Applied Bayesian Modeling course covers them.
Live online, Nov 2 - Dec 2
https://t.co/tWlYsNPlv0
π Same formula, different question.
Probability asks: If I know [p], how likely is the data?
Likelihood asks: Given the data, which [p] makes it most plausible?
A subtle distinction that lies at the heart of statistical inference and Bayesian thinking. π²π #Statistics #Bayesian
![JuanluCaba_Unex's tweet photo. π Same formula, different question.
Probability asks: If I know [p], how likely is the data?
Likelihood asks: Given the data, which [p] makes it most plausible?
A subtle distinction that lies at the heart of statistical inference and Bayesian thinking. π²π #Statistics #Bayesian https://t.co/nIrDVGWgZh](https://pbs.twimg.com/media/HT7ECl4WcAEEvPC.jpg)
How do ageing-related associations vary across space and time?
BSTVC | Spatiotemporal Interpretability: local patterns, global contributions, dynamic prediction.
Figures: Wan et al. (2022).
https://t.co/JXLS2BpEjs
https://t.co/XEbhqRfGRJ
#Bayesian #SpatialDataScience
Free WORKSHOP: #Bayesian Modeling in Practice: A Hands-On Introduction with #Stan by @djsyclik - one of the original developers of Stan!
Thu, Oct 1, 2026 9:30 AM - 12:00 PM EDT
@mcmc_stan #RStats
Register:
https://t.co/beQBXiYGId
#statstab #626 Goal-Driven Flexible Bayesian Design
Thoughts: Bayes allows you to design informative studies and anticipate issues.
#bayesian #bayes #design #simulation #rct #tutorial #inference #mcid #equivalence #efficacy #estimation #noninferiority
https://t.co/bJMHtJIlvv
#BJA editorial by Sidebotham explaining why #anaesthesia research should rely on #Bayesian probabilities, rather than #frequentist probabilities, to achieve clinically meaningful #inference statistics.
https://t.co/IQHTjqsT4s
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