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A continuous mapping theorem for the argmin-set functional with applications to convex stochastic processes

Dietmar Ferger (2021)


For lower-semicontinuous and convex stochastic processes Z n and nonnegative random variables ϵ n we investigate the pertaining random sets A ( Z n , ϵ n ) of all ϵ n -approximating minimizers of Z n . It is shown that, if the finite dimensional distributions of the Z n converge to some Z and if the ϵ n converge in probability to some constant c , then the A ( Z n , ϵ n ) converge in distribution to A ( Z , c ) in the hyperspace of Vietoris. As a simple corollary we obtain an extension of several argmin-theorems in the literature. In particular, in...

A strong invariance principle for negatively associated random fields

Guang-hui Cai (2011)

Czechoslovak Mathematical Journal

In this paper we obtain a strong invariance principle for negatively associated random fields, under the assumptions that the field has a finite ( 2 + δ ) th moment and the covariance coefficient u ( n ) exponentially decreases to 0 . The main tools are the Berkes-Morrow multi-parameter blocking technique and the Csörgő-Révész quantile transform method.

A uniform central limit theorem for dependent variables

Konrad Furmańczyk (2009)

Applicationes Mathematicae

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.

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