1) mutually independence random variables
互相独立随机变量
2) arrays of independent random variables
相互独立随机变量阵列
3) uncorrelated independent random variable
不相关独立随机变量
4) independent random variables
独立随机变量
1.
On the Basis of a these results, the Egorov s results for independent random variables are generalized to the case of negatively associated random variables.
给出了具有不同分布的NA随机变量列满足的若干强大数律;作为应用,不仅将独立随机变量的一类强极限定理完整的推广到NA随机变量情形,而且关于NA随机变量的一些已有结果可以作为推论得出。
2.
According to the Wittman strong law of large numbers of independent random variables,the Wittman strong law of large numbers of PA random variables sequences is extanded so that some deductions are obtained in this paper.
文章根据独立随机变量序列的Wittmann型强大数律,推广到PA序列的Wittmann型强大数律,并且由此得到一些相关的推论。
3.
In this paper,we consider asymptotic structure for the product of partial sums of independent random variables.
假设X1,X2,…,Xn,…为二阶矩存在的非负独立随机变量列,证明收敛性nk=1!μSkk"#1γk$%1&Tn→d e&2N成立,其中N是标准正态随机变量,Sk=ki=1(Xi,μk=E(Sk),σk=Var(Sk),γk=σk/μk,且Tn=nk=1(k/σk。
5) Independent Random Variable
独立随机变量
1.
Central Limit Theorems of Independent Random Variables;
独立随机变量的中心极限定理
2.
Formula of density function of sum of independent random variable of uniform distribution;
服从均匀分布的多个独立随机变量和的密度函数公式
3.
Let {Xn,n≥1} be independent random variables in a real separable Banach space,and the Chung-Teicher type conditions for the SLLN under the assumptions that the weak laws of large numbers hold were doscissed,which is b-1n∑nk=1(Xk-EXkI(‖Xk‖≤bk))p0 holds if and only if b-1n∑nk=1(Xk-EXkI(‖Xk‖≤bk))a.
设{Xn,n≥1}是实可分Banach空间独立随机变量,讨论了在弱大数律的假设下使得Chung-Teicher型强大数律也成立,即bn-1∑nk=1(Xk-EXkI(‖Xk‖≤bk))p0当且仅当bn-1∑nk=1(Xk-EXkI(‖Xk‖≤bk))a。
补充资料：互相
副词，表示彼此同样对待的关系：～尊重 ㄧ～帮助ㄧ～支持。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条