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Bayesian statistics and modelling
Bayesian statistics is an approach to data analysis based on Bayes' theorem, where
available knowledge about parameters in a statistical model is updated with the information …
available knowledge about parameters in a statistical model is updated with the information …
An extensive experimental survey of regression methods
Regression is a very relevant problem in machine learning, with many different available
approaches. The current work presents a comparison of a large collection composed by 77 …
approaches. The current work presents a comparison of a large collection composed by 77 …
Embers of autoregression: Understanding large language models through the problem they are trained to solve
RT McCoy, S Yao, D Friedman, M Hardy… - ar** clinical prediction models. Developers of such models often rely on an Events …
Moving beyond noninformative priors: why and how to choose weakly informative priors in Bayesian analyses
Throughout the last two decades, Bayesian statistical methods have proliferated throughout
ecology and evolution. Numerous previous references established both philosophical and …
ecology and evolution. Numerous previous references established both philosophical and …
Visualization in Bayesian workflow
Bayesian data analysis is about more than just computing a posterior distribution, and
Bayesian visualization is about more than trace plots of Markov chains. Practical Bayesian …
Bayesian visualization is about more than trace plots of Markov chains. Practical Bayesian …