Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strat...

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Adventures with a cultural Copilot

Abstract. Bayesian data analysis is about more than just computing a posterior distribution, and Bayesian visualization is about more than trace plots of M

The Bayesian approach to data analysis provides a powerful way to handle uncertainty in all observations, model parameters, and model structure using probability theory. Probabilistic programming lang...

Experiments in research on memory, language, and in other areas of cognitive science are increasingly being analyzed using Bayesian methods. This has been facilitated by the development of probabilist...

With the recent development of easy-to-use tools for Bayesian analysis, psychologists have started to embrace Bayesian hierarchical modeling. Bayesian hierarchical models provide an intuitive account ...

Throughout the last two decades, Bayesian statistical methods have proliferated throughout ecology and evolution. Numerous previous references established both philosophical and computational guideli...

A key step in the Bayesian workflow for model building is the graphical assessment of model predictions, whether these are drawn from the prior or posterior predictive distribution. The goal of these ...

This Primer on Bayesian statistics summarizes the most important aspects of determining prior distributions, likelihood functions and posterior distributions, in addition to discussing different appli...

In this guide, we present a reading list to serve as a concise introduction to Bayesian data analysis. The introduction is geared toward reviewers, editors, and interested researchers who are new to B...

This article explains the foundational concepts of Bayesian data analysis using virtually no mathematical notation. Bayesian ideas already match your intuitions from everyday reasoning and from tradit...

This Tutorial explains the statistical concept known as likelihood and discusses how it underlies common frequentist and Bayesian statistical methods. The artic...

A new major version of ggplot2 has been released on CRAN. Find out what is new here.

A collection of articles from the publisher of Nature that discusses statistical issues biologists should be aware of and provides practical advice to improve the statistical rigor and reproducibility...

Appropriate sample sizing, selection of controls in case-control studies, and clear end-points and interpretation of subgroup analyses are crucial for robust epidemiological research.

Increasing demands on the time of clinicians today reduce their opportunities to stay abreast of medical literature, and many report that they cannot read the literature critically. Information on res...

Ninth Edition T D V Swinscow Revised by M J Campbell, University of Southampton Copyright BMJ Publishing Group 1997 NB: Readers occasionally point out errors in this book and remind us that there ...

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This document provides a comprehensive introduction to the `epidist` package, a specialized R package for estimating epidemiological delay distributions using Bayesian methods. The package addresses k

A community to discuss epinowcast and real-time infectious disease analysis more generally

A Conference on Infectious Disease Dynamics. IDDconf is the second instalment of a new meeting series focussing on innovative research in infectious disease dynamics.

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Primary event censored distributions. Contribute to epinowcast/primarycensored development by creating an account on GitHub.