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Content available remote On exact strong laws of large numbers under general dependence conditions
EN
We study the almost sure convergence of weighted sums of dependent random variables to a positive and finite constant, in the case when the random variables have either mean zero or no mean at all. These are not typical strong laws and they are called exact strong laws of large numbers. We do not assume any particular type of dependence and furthermore consider sequences which are not necessarily identically distributed. The obtained results may be applied to sequences of negatively associated random variables.
2
Content available remote Exact strong laws of large numbers for independent random fields
EN
Let {Xṉ, ṉ ϵ Nd} be a family of independent random variables with multidimensional indices (a random field) with the same distribution as the r.v. X. A necessary and sufficient condition for the strong law of large numbers in this setting is E|X| logd-1+|X| < ∞. Our goal is to study the almost sure convergence of normalized or weighted sums in the case when this moment condition is not satisfied.
3
Content available remote Small deviation probabilities of weighted sums with fast decreasing weights
EN
We examine small deviation probabilities of weighted sums of i.i.d. positive random variables whose distribution function is regularly varying at zero provided that weights are decreasing fast enough.
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