Bayesian probability is a statistical method that applies probability to incorporate prior knowledge or beliefs when making predictions. Unlike traditional probability, which treats each event as ...

Spatial variability and uncertainty associated with soil volumetric moisture content (SVMC) is crucial in moisture prediction accuracy, this paper sets out to address this point of SVMC by developing ...

Latent Gaussian models (LGMs) are a staple in the statistical modeling toolkit, especially valuable when dealing with data that exhibits complex, hidden patterns. For engineers, think of LGMs as the ...

The human gut microbiota is considered a major modulator of the immune system during development 3 and in health and disease 8,9. For example, preterm infants have distinct microbiome compositions and ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

If you're looking for the material for a specific conference tutorial, navigate to the notebooks directory and look for a subdirectory for the conference you're interested. For example, notebooks/ODSC ...

This repository contains Python/PyMC3 code for a selection of models and figures from the book 'Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan', Second Edition, by John Kruschke (2015 ...