Discover and read the best of Twitter Threads about #Bayesian
Most recents (24)
1/ Bayesian inference is a powerful statistical framework that allows us to estimate the probability distribution of parameters based on data and prior knowledge. And R has a variety of packages for implementing Bayesian analysis! #rstats #datascience #Bayesian
#Incident reporting should follow & precede #riskmanagement?
The two are slightly different areas of specialization
in the office environment.
It is akin to the debate between #reliability and #safety.
Both are contrasting concepts in organizational #resilience studies.
The two are slightly different areas of specialization
in the office environment.
It is akin to the debate between #reliability and #safety.
Both are contrasting concepts in organizational #resilience studies.
They are certain leading businesses including big banks that have separated incident reporting desks from risk management co-ordination cells.
Actually, incidents are events which require an eye and a taxonomy for recognition.
Coding outcome events into loss database is essential
Actually, incidents are events which require an eye and a taxonomy for recognition.
Coding outcome events into loss database is essential
The most difficult area in financial risk management was the coding of operational risk incidents or potential events having adverse negative probabilistic outcomes, which can yield material quantifiable losses in the financial statements.
@BIS_org changed the AMA RiskMetrics
@BIS_org changed the AMA RiskMetrics
Now Harm-Jan De Grooth "Understanding Bayesian Analysis"
- more specifically "Bayesian Trial analysis"
@ESICM #datascience #ai #ml #icudata #bayesian
- more specifically "Bayesian Trial analysis"
@ESICM #datascience #ai #ml #icudata #bayesian
@ESICM Trials are now using Bayesian analysis or at least in secondary analysis.
pubmed.ncbi.nlm.nih.gov/30347031/
But also NEJM IL-6 in covid - purely bayesian analysis.
pubmed.ncbi.nlm.nih.gov/30347031/
But also NEJM IL-6 in covid - purely bayesian analysis.
Are there any changes in #brain #structure during the first year following #trauma #exposure? Is there a difference between individuals who develop #chronic #PTSD and those who #recover? A quick thread about our work published today in @molpsychiatry📜🧠🧵
nature.com/articles/s4138…
nature.com/articles/s4138…
Reduced #hippocampus and #amygdala volumes have been repeatedly documented in #PTSD patients. But do they reflect a #pretrauma vulnerability trait or #postexposure stress-induced atrophy?
To answer this question, we examined the association between #longitudinal #volumetric #changes of the hippocampus and the amygdala, as well as their #key #subregions, and #PTSD #symptom #trajectories during the first #14months following #trauma exposure. 
"Argument-Making in the Wild"
Today's SFI Seminar by Simon DeDeo (@LaboratoryMinds), streaming now. Follow our thread for pull quotes and slides:
Today's SFI Seminar by Simon DeDeo (@LaboratoryMinds), streaming now. Follow our thread for pull quotes and slides:
First, let's divide human history into three eras, or regimes of #knowledge #production and #consumption:
• #premodern/#archaic
• #modern + #postmodern
• the #egregore (online content sharing)
• #premodern/#archaic
• #modern + #postmodern
• the #egregore (online content sharing)
• The premodern era is defined by caloric restriction.
• The modern era is characterized by a small number of sellers of #information vs. a large number of consumers (see also #HerbertSimon's remarks on the "poverty of #attention")
• The modern era is characterized by a small number of sellers of #information vs. a large number of consumers (see also #HerbertSimon's remarks on the "poverty of #attention")
1. The impact case study (with .@MartinNeil9) on our #Bayesian network applications that was chosen as part of the .@QMUL #REF2021 submission achieved the highest possible rating 4*. Normally it’s not possible to know the rating for individual submissions...
2. Reason we know is because the QM Computer Science impact results were ranked joint top in the country – with 100% 4* ratings (so all 6 CS submissions were rated 4*). Here's a public summary of our case study from QM Press Office (apologies for typos!) eecs.qmul.ac.uk/research/featu…
3. The full submission included testimonies about critical applications with international organizations that cannot be made public because of confidentiality. The #Bayesian network software referred to is .@AgenaRisk agenarisk.com
I've been studying #Bayesian methods in #rstats since the beginning of this year.
The more I learn, the more excited I get about Bayesian.
Here's why...
The more I learn, the more excited I get about Bayesian.
Here's why...
One of the key R packages I've been experimenting with is BRMS (Bayesian Regression Models using Stan).
BRMS allows us to model a wide range of statistical models including:
- linear,
- count data,
- survival,
- multi-effects,
- non-linear (& more!)
BRMS allows us to model a wide range of statistical models including:
- linear,
- count data,
- survival,
- multi-effects,
- non-linear (& more!)
The important point is that Bayesian modeling implements a special technique called Markov Chain Monte Carlo (MCMC).
MCMC is a game changer.
MCMC is a game changer.
2/n In business, I've made great regression models that have predicted how much sales we were going to make.
In fact, this helped me increase revenue from $3M to $15,000,000 per year at one of the companies I worked at.
BUT my models were NOT perfect.
In fact, this helped me increase revenue from $3M to $15,000,000 per year at one of the companies I worked at.
BUT my models were NOT perfect.
3/n In fact, I'd argue that the BIGGEST flops were due to over-confidence.
Believing my model was better than it actually was.
Here's what hurt me...
Believing my model was better than it actually was.
Here's what hurt me...
The language of quant crit is in its infancy but the practice has a long legacy dating back to Du Bois and Wells-Barnett.
Let's use #QuantCritSyllabus to feature studies that use critical quantitative methodologies and frameworks. I'll start.
#AcademicTwitter #SocAF #QuantCrit
Let's use #QuantCritSyllabus to feature studies that use critical quantitative methodologies and frameworks. I'll start.
#AcademicTwitter #SocAF #QuantCrit
The Racism-Race Reification Process: A Mesolevel Political Economic Framework for Understanding Racial Health Disparities by @aasewell
#QuantCritSyllabus #HealthDisparities #MortgageMarkets
#MergedDatabases #Multilevel #GeneralizedLinearModels
journals.sagepub.com/doi/abs/10.117…
#QuantCritSyllabus #HealthDisparities #MortgageMarkets
#MergedDatabases #Multilevel #GeneralizedLinearModels
journals.sagepub.com/doi/abs/10.117…
Collateral Damage: The Health Effects of Invasive Police Encounters in New York City by @aasewell & Kevin Jefferson
#QuantCritSyllabus #Health #Policing
#NYC #CommunityHealthSurvey #StopQuestionandFrisk #MultilevelModels
link.springer.com/article/10.100…
#QuantCritSyllabus #Health #Policing
#NYC #CommunityHealthSurvey #StopQuestionandFrisk #MultilevelModels
link.springer.com/article/10.100…
Volume 100 of @jstatsoft: Software for Bayesian Statistics
Guest editors: @micameletti & @precariobecario
20 contributions on a wide range of methods #rstats #python #bayesian #inla @mcmc_stan #nimble #brms #rjags
URL: jstatsoft.org/v100
Guest editors: @micameletti & @precariobecario
20 contributions on a wide range of methods #rstats #python #bayesian #inla @mcmc_stan #nimble #brms #rjags
URL: jstatsoft.org/v100
Van Niekerk, Bakka, Rue, Schenk:
New Frontiers in Bayesian Modeling Using the INLA Package in R
#rstats #inla #bayesian
doi.org/10.18637/jss.v…
New Frontiers in Bayesian Modeling Using the INLA Package in R
#rstats #inla #bayesian
doi.org/10.18637/jss.v…
Michaud, De Valpine, Turek, Paciorek, Nguyen:
Sequential Monte Carlo Methods in the nimble and nimbleSMC R Packages
#rstats #bayesian #nimble
doi.org/10.18637/jss.v…
Sequential Monte Carlo Methods in the nimble and nimbleSMC R Packages
#rstats #bayesian #nimble
doi.org/10.18637/jss.v…
1/ Excited to share how T cell therapies kill #leukemia!! multi-omics + new #computational #singlecell tools for longitudinal analysis 👉unexpected answer! cell.com/cell-reports/f…
*👏* @elhamazizi! 🙏 @dpeer Cathy Wu @MDAndersonNews @CPRITTexas @ColumbiaBME @sloan_kettering
*👏* @elhamazizi! 🙏 @dpeer Cathy Wu @MDAndersonNews @CPRITTexas @ColumbiaBME @sloan_kettering
2/ We studied donor lymphocyte infusion (DLI) - an #Immunotherapy for relapsed #leukemia after #BMT & the #og of #celltherapy. Previously, we showed DLI reversed T cell exhaustion - but didn't know why/how/which T cells were responsible...
ashpublications.org/blood/article/…
ashpublications.org/blood/article/…
3/ To address these ?'s, we modeled intraleukemic T cell dynamics by integrating longitudinal, multimodal data from ~100K T cells (!) during response (R) or resistance (NR: nonresponder) to DLI.
Nebraska Attorney General's October 14 legal opinion on prescribing Ivermectin cites our #Bayesian analysis (page 16 & footnotes 101 and 104). Rules that it can be prescribed with informed consent ago.nebraska.gov/sites/ago.nebr…
2/3: This is the American Journal of Therapetics letter that was cited: dx.doi.org/10.1097/MJT.00…
3. But the conclusions of such studies are also confounded by failing to consider non-Covid deaths; this overestimate the safety of the vaccine if there were serious adverse reactions. In fact multiple confounding factors will overestimate vaccine effectiveness.
4. One factor is how/whether a person is classified as a Covid ‘case’, Covid ‘hospitalization’ & Covid ‘death’. These can differ between vacc & unvaccinated. The unvaccinated who die ‘with’ as opposed to ‘from’ Covid are more likely to be classified as Covid deaths.
5. Another critical factor is how/whether a person is classified as ‘vaccinated’. Any person testing positive for Covid or dying of any cause within 14 days of their second dose is now classified by the CDC as ‘unvaccinated’
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I'm very happy that we (finally) got an acceptance for our submitted paper in the Journal of Open Source Education, JOSE🙂.
"An open source crash course on parameter estimation of computational models using a Bayesian optimization approach"
doi.org/10.21105/jose.…
I'm very happy that we (finally) got an acceptance for our submitted paper in the Journal of Open Source Education, JOSE🙂.
"An open source crash course on parameter estimation of computational models using a Bayesian optimization approach"
doi.org/10.21105/jose.…
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Parameter estimation is a crucial aspect of model development in science and engineering. In the proposed educational module, we have a look at the #Bayesian optimization processes in general and model calibration (parameter estimation) in particular.
Parameter estimation is a crucial aspect of model development in science and engineering. In the proposed educational module, we have a look at the #Bayesian optimization processes in general and model calibration (parameter estimation) in particular.
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For demonstration purposes, we implement a model parameter estimation process for a fitting problem step by step in Python such that the readers can adapt it to their own models and use-cases.
Codes are available in this repo: github.com/mbarzegary/edu…
For demonstration purposes, we implement a model parameter estimation process for a fitting problem step by step in Python such that the readers can adapt it to their own models and use-cases.
Codes are available in this repo: github.com/mbarzegary/edu…
Work. #childhoodcancer
Are you a part of this SME group, @davidcnorrismd?
Trial design and biostats folks, your expertise is needed. DM me for details on how to join this SME group. #biostats #trialdesign #bayesian #ChildhoodCancer
If the connotation of risk is an intertwined concept and is difficult to quantify, how does a Risk Officer look at it?
Is there any way other than using copula models to determine systemic risk with long tails or a black swan event?
@CQFInstitute @GARP_Risk @SOActuaries
Is there any way other than using copula models to determine systemic risk with long tails or a black swan event?
@CQFInstitute @GARP_Risk @SOActuaries
I guess we are worried about Market and Credit Risks or other interrelated financial risks which can create conjoint loss given events.
Any #Gaussian distribution model will enable you to model and predict potential Operational, Liquidity and Balance sheet AL - (Asset - liability) Mismatch, Market and Credit drove losses under normal market conditions.
*NEW THREAD* This week we’ll be featuring the top 5 most impactful articles published in @RSeriesa in 2020 as captured by @altmetric
We’ll feature one paper per day in reverse order tarting by our 5th place
🧵👇🏽
1/n
We’ll feature one paper per day in reverse order tarting by our 5th place
🧵👇🏽
1/n
Top 5th most impactful paper: Ellison et al: doi.org/10.1111/rssa.1…
*CONTEXT* Fertility projections are a key determinant of population forecasts, which are widely used by government policy makers and planners
2/n
*CONTEXT* Fertility projections are a key determinant of population forecasts, which are widely used by government policy makers and planners
2/n
*AIM* Propose an intuitive and transparent hierarchical #Bayesian model to forecast cohort fertility
*METHOD* Use of hamiltonian Monte Carlo methods and a data set from the human fertility database
3/n
*METHOD* Use of hamiltonian Monte Carlo methods and a data set from the human fertility database
3/n
THREAD* We continue featuring the top 10 most cited articles published in @RSeriesa in 2020
Day 3: today we featured articles ranked 4th & 5th on the topics of #shipping 🚢 & #slavery
🧵starting👇🏽
1/n
Day 3: today we featured articles ranked 4th & 5th on the topics of #shipping 🚢 & #slavery
🧵starting👇🏽
1/n
The first article is by Silverman: doi.org/10.1111/rssa.1…
*CONTEXT* Quantifying hidden populations such as victims of modern slavery is challenging; yet, needed to develop strategies leading to legislation, inc. the Modern Slavery Act 2015
2/n
*CONTEXT* Quantifying hidden populations such as victims of modern slavery is challenging; yet, needed to develop strategies leading to legislation, inc. the Modern Slavery Act 2015
2/n
*AIM* Investigate the stability and robustness of various multiple‐systems‐estimate methods to measure modern slavery using Kosovo 🇽🇰as case study
*METHOD* Use of multiple‐systems‐estimate methods to develop a new Markov chain Monte Carlo #Bayesian approach
3/n
*METHOD* Use of multiple‐systems‐estimate methods to develop a new Markov chain Monte Carlo #Bayesian approach
3/n
Thrilled to announce our new paper by Victoria Junquera and Adrienne Grêt-Regamey, "Assessing livelihood vulnerability using a Bayesian network: a case study in northern #Laos”, is now out in @ecologyandsociety1 ecologyandsociety.org/vol25/iss4/art… #openaccess #WomenInSTEM. Short thread👇
This work analyzes the effect of #cashcrop production on livelihood #vulnerability, which we define in terms of the probability distribution of household income.
We use a #Bayesian network to estimate the probability distribution of household income, conditional on biophysical (e.g., yield), household (e.g., agricultural land), and commodity price variables.
Today's talk is with neuroscientist #KarlFriston of @ucl, who will offer a heuristic proof suggesting that life is an inevitable emergent property of any weakly mixing random dynamical system that possesses a #Markov blanket.
Tune in here at 12:15 PM MT:
santafe.edu/events/me-and-…
Tune in here at 12:15 PM MT:
santafe.edu/events/me-and-…
...and because it's 2020 and nothing is ever simple, we are having technical issues with the stream. The talk is recorded and we will upload it across all of our platforms ASAP. Our apologies!
Spatial boundaries are statistical boundaries: #KarlFriston on #MarkovBlankets, the reciprocal interfacing between internal and external states.
Follow this thread for more highlights from the talk and stay tuned for the video link...
Follow this thread for more highlights from the talk and stay tuned for the video link...
Chapter 4: Head rotation sensation is a splendid example of dynamic #Bayesian multisensory fusion since it involves several sensors with different dynamics. These sensor can be put in conflict or switched on/ off experimentally. Follow the tour! #vestibular
2/ We have (at least) 3 rotations sensors with different dynamics: the inner ear's canals detect acceleration; vision velocity, and graviceptors position (when rotating in vertical planes). The brain also relies on a zero velocity prior. Looks like a job for a #Kalmanfilter!
3/ I will explain (&simulate) motion perception during constant velocity rotations (starting from 0 velocity at t=0). Each sensor can report the motion, or 0, or be off altogether. There's experiments in the literature covering nearly all combinations! This will be a long thread!
(1/n) I’ve been following discussions of #Bayesian sequential analyses, type I error, alpha spending etc. At the risk of offending everyone (please be kind!), I see reasons Bayesian sponsors and regulators can still find value in type I error rates and so forth.
(2/n) I’m focused on the design phase. After the trial, the data is the data. Lots of good stuff has been written on the invariance of Bayesian rules to stopping decisions. But in prospectively evaluating a trial design, even for a Bayesian there is a cost to interims, etc.
(3/n) Example…ultra simple trial. Normally distributed data. Known sigma=2. Mean is either 0 (null) or 1 (good). Simple decision space at end of trial…approve or not. A Bayesian utility would place values over the 4 combinations of truth/decision.
Chapter 1: Why do we feel #dizzy when turning? This is because of how out inner ear’s rotation sensors (#vestibular semi-circular canals) work, from a mechanical point of view. Watch these movies and the next for explanations.
2/ The inner ear's #vestibular semi-circular canals are liquid-filled tubes. When the head rotates, the liquid stays in place and flows in the canal. This activates hair cells (in a structure called cupula) that sense the rotation.
3/ However, when turning too much, the liquid starts to rotate with the canal and the rotation signal fades out. Furthermore, when the rotation stops, the liquid keeps flowing and creates a rotation after-effect.
~ New Post ~
During this quarantine time, I binge-watched @Stanford #CS330 lectures taught by the brilliant @chelseabfinn. This blog post is a summary of the key takeaways on #Bayesian Meta-Learning that I’ve learned. #AtHomeWithAI
medium.com/cracking-the-d…
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During this quarantine time, I binge-watched @Stanford #CS330 lectures taught by the brilliant @chelseabfinn. This blog post is a summary of the key takeaways on #Bayesian Meta-Learning that I’ve learned. #AtHomeWithAI
medium.com/cracking-the-d…
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Bayesian meta-learning generates hypotheses about the underlying function, samples from the data distribution, and reasons about model uncertainty. It is suitable for problems in safety-critical domains, exploration strategies for meta-RL, and active learning.
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There are various Bayesian Meta-Learners pre-neural-nets:
- @drfeifei, @rob_fergus, and @PietroPerona: vision.stanford.edu/documents/Fei-…
- @rsalakhu, @wise_tbaum, and Torralba: proceedings.mlr.press/v27/salakhutdi…
- @LakeBrenden, @rsalakhu, and @wise_tbaum: papers.nips.cc/paper/5128-one…
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- @drfeifei, @rob_fergus, and @PietroPerona: vision.stanford.edu/documents/Fei-…
- @rsalakhu, @wise_tbaum, and Torralba: proceedings.mlr.press/v27/salakhutdi…
- @LakeBrenden, @rsalakhu, and @wise_tbaum: papers.nips.cc/paper/5128-one…
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