Open-source tools have made MMM more accessible, but reliable results still depend on clean data, thoughtful modeling, and ...

Background Antimicrobial resistance (AMR) is an escalating global health crisis being worsened by climate change. Studies of ...

Genome-wide association studies (GWAS) have catalogued hundreds of thousands of genetic variants linked to complex human traits and diseases, with more than 625,000 variant-trait associations across ...

Bayesian methods are becoming an increasingly popular approach to data analysis across a wide range of research fields. They offer a flexible and structured framework for statistical inference, ...

Abstract: Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switching linear ...

Abstract: In this letter, we present a unified Bayesian inference framework for generalized linear models (GLM), which iteratively reduces the GLM problem to a sequence of standard linear model (SLM) ...

Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...

a.s.ist today announced the launch of a 7-day free trial for AutoStatSpectra, its Bayesian-statistics-based spectral analysis software. During the trial period, all features will be available without ...

Bayesian statistical models use prior data to update the probability of a hypothesis as new evidence emerges. Image credit: PeopleImages / Shutterstock.com Bayesian statistical models could help ...

Pull request by Ben Goodrich for fixing the issue with clang4. New version on it's way to CRAN.

Bayesian regression with linear basis function models. Introduction to Bayesian linear regression. Implementation with plain NumPy and scikit-learn. See also PyMC3 implementation. Gaussian processes.