Bayesian statistics, by contrast, provide conditional probabilities of parameter values — the plausibility of different parameter values — given the data.

Bayesian analyses are increasingly being used in genetics, particularly in the context of genome-wide association studies. This article provides a guide to using Bayesian analyses for assessing ...

Reisz talks with Mike Lee Williams of Cloudera’s Fast Forward Labs about Probabilistic Programming. The two discuss how Bayesian Inference works, how it’s used in Probabilistic Programming.

Bayesian inference for causal effects follows from finding the predictive distribution of the values under the other assignments of treatments. This perspective makes clear the role of mechanisms that ...

Stan is a free and open-source C++ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia and ...

Methods We propose a simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit trade-off.