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On the rates of convergence for sums of dependent random variables
Published 20 Nov 2020 in math.PR | (2011.10262v1)
Abstract: For a sequence ${X_{n}, \, n \geqslant 1 }$ of nonnegative random variables where $\max[\min(X_{n} - s,t),0]$, $t > s \geqslant 0$, satisfy a moment inequality, sufficient conditions are given under which $\sum_{k=1}n (X_k - \mathbb{E} \, X_k)/b_n \overset{\mathrm{a.s.}}{\longrightarrow} 0$. Our statement allows us to obtain a strong law of large numbers for sequences of pairwise negatively quadrant dependent random variables under sharp normalising constants.
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