Abstract:
By a sequence of random vectors {ζk}, we can construct empirical distributions of the type Qn=(logn)−1∑nk=1δζk/k. Statements on the convergence of these or similar distributions with probability 1 to a limit distribution are called almost sure theorems. We propose several methods which permit us to easily deduce the almost sure limit theorems from the classical limit theorems, prove the invariance principle of the type “almost sure” and investigate the convergence of generalized moments. Unlike the majority of the preceding papers, where only convergence to the normal law is considered, our results may be applied in the case of limit distributions of the general type.
Keywords:
limit theorems, convergence almost sure, sums of independent variables, weak dependence, invariance principle.
Citation:
I. A. Ibragimov, M. A. Lifshits, “On almost sure limit theorems”, Teor. Veroyatnost. i Primenen., 44:2 (1999), 328–350; Theory Probab. Appl., 44:2 (2000), 254–272
This publication is cited in the following 34 articles:
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