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Common sense says that what you believe after seeing new data should be some sort of compromise between what you believed before and what the new data says. You don’t want to ignor...
I took a look at the above-titled book by economists Duncan Foley and Ellis Scharfenaker. It’s an interesting read, in many ways a throwback to the 1950s when a group of mathematic...
Почему одни люди точнее прогнозируют будущее, чем другие? Дело не только в интеллекте или объёме информации. Главное преимущество суперпрогнозистов - байесовское мышление: новая ин...
An intuitive introduction to reasoning with uncertainty, from directed Bayesian networks to undirected Markov networks and weighted logical rules. The post Bayesian Networks and Ma...
A few days ago I wrote a post entitled Does additional data always reduce posterior variance?. In a nutshell, the answer is no, not always. That led the previous post which looked...
Esmeralda Whitammer, Sara Wade, Vincent Fortuin, Konstantina Palla, and Theodore Papamarkou write: We are organising a focused workshop on Rethinking the Role of Bayesianism in the...
We’re very excited about this book. It’s the result of several years of effort. You can order from the publisher or from Amazon. Here’s the book’s webpage, which includes the data...
We’ve talked about uncertainty in polls (see Margin of Error, Total Margin of Error, Total Margin of Error II) and we’ve talked about ranked data (see exploded logit !). A new pape...
A model is almost never 100% sure of anything. These 10 probability concepts explain how it makes decisions anyway.
New FDA guidance on the use of Bayesian statistics signals a broader shift in accommodating more flexible clinical trial designs and the complexities of diseases such as certain ca...
This post is from Bob. I’ve been thinking a lot about scores (gradients of the log density function) and how they can be used for convergence monitoring. We know that the expected...
Due tomorrow (June 10): Enter a contest for Alexandre Andorra’s interview of Aki, Richard, and Andrew about their new book Bayesian Workflow. I hope folks ask about evaluating MRP...
Ryan Giordano, Alice Cima, Jared Murray, Erin Hartman, and Avi Feller write: Multilevel regression and poststratification (MrP) has become a workhorse method for estimating populat...
by Dhorasso Temfack, Jason Wyse Estimating latent epidemic states and model parameters from partially observed, noisy data remains a major challenge in infectious disease modeling...
by David J. Warne, Xiangrun Zhu, Thomas P. Steele, Stuart T. Johnston, Scott A. Sisson, Matthew Faria, Ryan J. Murphy, Alexander P. Browning Biological systems exhibit substantial...
Using artificial intelligence to decide where the next Euro goes.Continue reading on Berlin Tech Blog (by mobile.de & Kleinanzeigen) »
Optimal Resolution in Histograms: A Rigorous Bayesian Approach to Density Fitting The post How to Mathematically Choose the Optimal Bins for Your Histogram appeared first on Toward...
In 2019, Andrew blogged about collinearity in Bayesian models. In the comments, he pointed to an example from Bayesian Data Analysis, 2nd edition (BDA2). I think it is a useful exa...
Last week we talked about The Big Changes Coming to the Times/Siena Poll: New weighting variable: support score = E(2024 vote | other X variables). New weighting method: energy bal...
This is Leo. Jonah Gabry (Stan developer, Andrew’s collaborator, etc.) is spending the whole month of May as a visiting professor here with us at the University of Trieste in Italy...
This one’s from 2019, but it’s worth reposting given recent interest in prediction markets. The story starts with a post from economist Greg Mankiw, who wrote: Who has the best cha...
A discussion over lunch today brought up the fact that additional data does not always decrease the size of a confidence interval. This post will look at this from a Bayesian persp...
How to Turn Simple Head-to-Head Choices Into Probabilistic Rankings The post Learning From Pairwise Preferences: An Introduction to the Bradley Terry Model appeared first on Toward...
The above sketch shows a decision tree. The circles are uncertainty nodes and the squares are decision nodes. Read the tree from left to right: to start, there is uncertainty of wh...
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