A weak law of large numbers for the weighted sums of non-identically distributed NA random matrix sequences is studied.
研究了不同分布NA序列加权和最大值的弱大数定律，推广了前人的结果。
Until now, all the results on central limit theorems under sublinear expectations require that the sequence of random variables is independent and identically distributed.
本文的目的是探究次线性期望理论中一个重要的结果：中心极限定理。
Benchmarks may also have non-identically-distributed observable variables that may affect performance.
基准测试还可能有非恒等分布的可观察到的变量，它们也会影响性能。
Benchmarks may also have non-identically-distributed observable variables that may affect performance.
基准测试还可能有非恒等分布的可观察到的变量，它们也会影响性能。
应用推荐