Stan
Stan is a probabilistic programming language and software platform for statistical modeling, data analysis, and Bayesian inference. It enables developers and statisticians to specify complex statistical models using a high-level language and perform efficient Bayesian computation through advanced algorithms like Hamiltonian Monte Carlo (HMC) and variational inference. Stan is widely used in fields such as machine learning, social sciences, and epidemiology for tasks like parameter estimation, prediction, and uncertainty quantification.
Developers should learn Stan when working on projects that require robust Bayesian statistical analysis, such as in data science, machine learning, or scientific research, where modeling uncertainty and complex dependencies is crucial. It is particularly useful for hierarchical models, time-series analysis, and cases where traditional frequentist methods are insufficient, as it provides a flexible framework for specifying custom probabilistic models and generating posterior distributions with high computational efficiency.