Invariance principles for self-similar set-indexed random fields

Abstract

For a stationary random field $(X_j)_{j\in\Z^d}$ and some measure m on $\R^d$, we consider the set-indexed weighted sum process $S_n(A)=\sum_{j\in\Z^d}m(nA\cap R_j)^\frac12 X_j$, where R_j is the unit cube with lower corner j. We establish a general invariance principle under a p-stability assumption on the X_j's and an entropy condition on the class of sets A. The limit processes are self-similar set-indexed Gaussian processes with continuous sample paths. Using Chentsov's type representations to choose appropriate measures m and particular sets A, we show that these limits can be Levy (fractional) Brownian fields or (fractional) Brownian sheets.