Stan

Stan is a probabilistic programming toolkit for sophisticated Bayesian statistical modeling, supporting everything from simple regression to complex hierarchical and time-series models, maintained by an active open-source developer community with its own annual conference (StanCon 2026, Uppsala, Sweden). It offers interfaces in Python, Julia, R, and Unix shell, runs across laptops, clusters, and cloud environments, and is supported by a rich ecosystem of companion validation and visualization tools built by the community around it. As a statistical modeling language rather than an end-user application, it requires real statistics and programming background to use — it's infrastructure for researchers and data scientists doing Bayesian analysis, not a point-and-click tool. Good fit for a statistician, researcher, or data scientist who needs rigorous Bayesian modeling capabilities across multiple languages rather than being locked into one statistical software ecosystem.