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- negatively associated random variables sequences NQD序列
- Negatively associated random variables NA随机变量
- Complete Convergence for a Class of Associated Random Variables 一类相关随机变量序列的完全收敛性
- The renewal theorem of negatively and positively associated random variables 负、正相协随机变量列的更新定理
- A Strong Law of the Large Numbers for Sequence of Negatively Associated Random Variables 负相协随机变量列的强大数律
- associated random variable sequence 相协随机变量序列
- The Strong Law of Large Number for Negatively Associated Random Variables without Stationary Distribution 不具有平稳分布的负相协随机变量的强大数定律
- associated random variables 相伴随机变量
- Almost sure convergence and a strong law of large numbers for the partial sum of associated random variable sequences 相协随机变量部分和的几乎处处收敛性和强大数定律
- A time series data set is a sequence of random variables indexed by time. 时间序列数据是以时间为指标的一个随机变量序列。
- An estimator is a random variable. 估计量是一个随机变量。
- The expected value of a random variable. 期望值随意可。
- In this paper, it is proved that two random variables' independence can infer their no-correlation and its untenable inverse proposition. 本文证明了由两随机变量的独立性可推出它们的不相关性，但逆命题不成立。
- The formula for empirical frequency correlation coefficient between two random variables is demon -strated. 导出了两随机变量的频率相关系教的公式。
- The Distribution of Quotient of Beta,Gamma Random Variables and Its Applications. Beta,Gamma随机变量之商的分布及其应用
- The problem of inconsistency of basic random variables between different failure modes was resolved. 解决了不同失效模式间基本随机变量不一致的问题；
- Sample Percentage Presentation of Joint Probability Density of Two Random Variables. 二维随机变数联合机率密度之取样百分比。
- In the first chapter,the relative background of PA random variables sequences is given. 第一章是绪论，主要介绍了PA随机变量序列的背景。
- In the following two chapters the resultes of PA random variables sequences are obtained. 第三、四章是本文的主体，得到了有关PA随机变量序列的结果。
- The Six Sigma Black Belt should be able to compute expected values for continuous and discrete random variables. 西格玛黑带应能计算出连续或离散随机变量的期望值。
