Stan
Stan is a probabilistic programming language and software platform for statistical modeling, data analysis, and Bayesian inference. It allows users to specify complex statistical models using a high-level modeling language and performs efficient Bayesian inference through advanced Markov chain Monte Carlo (MCMC) sampling algorithms like Hamiltonian Monte Carlo (HMC) and variational inference. Stan is widely used in academia, research, and industry for tasks such as parameter estimation, uncertainty quantification, and predictive modeling.
Developers should learn Stan when working on projects that require robust Bayesian statistical analysis, such as in data science, machine learning, epidemiology, or economics, where handling uncertainty and complex hierarchical models is crucial. It is particularly valuable for applications like A/B testing, time-series forecasting, and causal inference, as it provides flexible model specification and reliable inference even with limited data or non-standard distributions.