论文标题

关于相关随机变量总和的收敛速率

On the rates of convergence for sums of dependent random variables

论文作者

da Silva, João Lita

论文摘要

对于序列$ \ {x_ {n},\,\,n \ geqslant 1 \} $的非负随机变量,其中$ \ max [\ max [\ min(x_ {n} - s,s,t),0] $,$ t> s \ geqslant 0 $,满足$ _ n $ suff Affe Affe Affe Aduse nduse n $ und,n $ sum_ c = k = k = k = \ Mathbb {e} \,x_k)/b_n \ Overset {\ Mathrm {a.s。}}} {\ LongrightArrow} 0 $。我们的陈述使我们能够获得强大的法律,以在尖锐的归一化常数下对成对的负象限随机变量的序列进行大量定律。

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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