Stochastic processes form the backbone of modern probability theory, describing systems that evolve randomly over time or space. They are instrumental in areas ranging from statistical physics to ...

This is a preview. Log in through your library . Abstract A set of n points in Euclidean space is partitioned into the k groups that minimize the within groups sum of squares. Under the assumption ...

This is a preview. Log in through your library . Abstract We prove a central limit theorem for the distance of the Brownian point on the universal cover of a compact negatively curved Riemannian ...

The Central Limit Theorem is a statistical concept applied to large data distributions. It says that as you randomly sample data from a distribution, the means and standard deviations of the samples ...

Stein's method has emerged as a powerful and versatile tool in probability theory for deriving error bounds in distributional approximations. Originally developed to ...