This is a preview. Log in through your library . Abstract For each $k = 1, 2, \cdots$ let $n = n(k)$, let $m = m(k)$, and suppose $y_1^k, \cdots, y_n^k$ is an $m ...

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 usual local central limit theorem provides an approximation for the probability for an iid sequence . The approximation is proportional to the lattice size of the underlying distribution of the ...

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 ...