Marc Dotson

@marcdotson.com

Causal Inference | Bayesian Statistics | Machine Learning // Husband, father, Latter-day Saint, assistant professor of data analytics, nerd. Blog: occasionaldivergences.com | GitHub: github.com/marcdotson

Thinking about how this might go Listener: My chains aren't converging Andrew: Your model is bad Aki: Your parameterization is bad Richard: The Buddha teaches us that numerical integration is suffering

Pierre-Simon Laplace@learnbayesstats.bsky.social · 2mo ago

🚨 @rmcelreath.bsky.social @statmodeling.bsky.social & @avehtari.bsky.social are coming on the show mid-June to discuss their new book, Bayesian Workflow! ONE listener gets to bring a real Bayesian problem onto the recording and have the three of them work through it live. Here's how to enter 🧵

This administrative attack on the nonprofit sector fits with a pattern of authoritarian restrictions on civil society that's been going on for the past decade+ @suparnac.bsky.social and I (and others) have done a bunch of research on this from an intl/comparative perspective #nonprofitsky #polisky 🧵

The Intercept@theintercept.com · 2y ago

The House is set to vote Tuesday on a bill that would let the administration destroy nonprofits it claims support terrorism.

The International Society for Bayesian Analysis tells me Statistical Rethinking has won the 2024 DeGroot Prize for its contributions to "statistical inference, decision theory and statistical applications". This is huge honor especially given the previous winners who have influenced me so much.

Cover of Statistical RethinkingWinners of the DeGroot Prize

2021
Nicolas Chopin and Omiros Papaspiliopoulos (2020). An Introduction to Sequential Monte Carlo. Springer.

2019
Subhashis Ghosal and Aad van der Vaart. Fundamentals of Nonparametric Bayesian Inference. Cambridge University Press.

2017
David Banks, Jesus Rios, and David Rios Insua.  Adversarial Risk Analysis.  CRC Press.

2015
Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin.  Bayesian Data Analysis, Third Edition.  CRC Press.

2013
Noel Cressie and Christopher Wikle (2011).  Statistics for Spatio-Temporal Data.  John Wiley and Sons.

Kevin P. Murphy (2012). Machine Learning: A Probabilistic Perspective. MIT Press.

2011
Jay Kadane (2011).  Principles of Uncertainty.  CRC Press.

2009
Giovanni Parmigiani and Lurdes Inoue (2009). Decision Theory: Principles and Approaches. John Wiley and Sons.

Carl Edward Rasmussen and Christopher K. I. Williams (2006). Gaussian Processes for Machine Learning (freely availa

~3 minute-long video looking at #positron's #rstats debugging capabilities. In short: browser() and traceback() are supported with a nice explorer. Positron engages the debug mode with red outline. Care is needed when engaging debugger. No script breakpoints yet (?) youtu.be/p_4ZS-nnQ2Q

Positron Debugger for R Demo with Nested Functions (Public Beta)

This is a quick demo video showing how the Positron R debugger works. In short, it primarily uses `browser()` and has support for `traceback()`. When the er...

youtu.be