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Basic notions of stochastic processes
Convergence of random elements
Properties of mixing processes
10 other sections not shown
absolutely regular analogous arbitrary assume Borel bounded called characteristic function choose compact complete conclusion consider constant continuous converges converges weakly Corollary defined definition denote density depending desired difference distribution function e-independent easily Example exists fact finite fixed following conditions following lemma following theorem Further given hand Hence holds identically implies independent inequality Lemma lim sup martingale matrix method mixing coefficient mixing condition o-algebra obtain obvious P(AB partition points positive integer positive numbers probability measures probability space Proof of Theorem properties prove random elements random variables random vectors Rd-valued relations Remark respect result satisfied sequence of random stable stationary sequence subsets sufficiently large sums Suppose tight values write