Generation of one-sided random dynamical systems by stochastic differential equations.
In this article, we study the approximation of a probability measure on by its empirical measure interpreted as a random quantization. As error criterion we consider an averaged th moment Wasserstein metric. In the case where , we establish fine upper and lower bounds for the error, a. Moreover, we provide a universal estimate based on moments, a . In particular, we show that quantization by empirical measures is of optimal order under weak assumptions.
Page 1