A characterization of the weak convergence of convolution powers
For lower-semicontinuous and convex stochastic processes and nonnegative random variables we investigate the pertaining random sets of all -approximating minimizers of . It is shown that, if the finite dimensional distributions of the converge to some and if the converge in probability to some constant , then the converge in distribution to in the hyperspace of Vietoris. As a simple corollary we obtain an extension of several argmin-theorems in the literature. In particular, in...
In this paper we obtain a strong invariance principle for negatively associated random fields, under the assumptions that the field has a finite th moment and the covariance coefficient exponentially decreases to . The main tools are the Berkes-Morrow multi-parameter blocking technique and the Csörgő-Révész quantile transform method.
Niemiro and Zieliński (2007) have recently obtained uniform asymptotic normality for the Bernoulli scheme. This paper concerns a similar problem. We show the uniform central limit theorem for a sequence of stationary random variables.