Generalized Wishart distribution

The Generalized Wishart distribution is a mathematical model used to describe the variability in multi-dimensional data, especially for random matrices that represent covariances or correlations. It extends the classical Wishart distribution by allowing more flexible structures and parameters, making it useful in multivariate statistics, finance, and machine learning for modeling uncertainty in covariance matrices. Essentially, it provides a probabilistic framework to describe how the relationships among multiple variables can vary, capturing complex dependencies and uncertainty in high-dimensional data.