sum of two random variables 二随机变量和
correlation between two random variables 两个随机变量的相关
covariance of two random variables 两个随机变量协方差
Two-dimensional random variables 二元随机变量
two-point random variables 服从两点分布的随机变量
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。
Then proves that this kind of random variables are the Markov chains with strong placidity by getting two kinds of expressions of the random variables combine distributing.
通过求得两种随机变量的联合分布的表达式,证明了此类随机变量序列是强平稳的齐次马尔科夫链。
In fact, the same relativity of two pair random variables possibly can have the different related pattern and the special part characteristic.
事实上,即使具有相同相关性强度的两对随机变量,也可能会因为有不同的相关模式和尾部特征而表现出完全不同的结构特点。
Covariance is--we'll call it--now we have two random variables, so cov... I'll just talk about it in a sample term.
协方差是...我们有两个随机变量,x和y的协方差是,从样本的角度来说
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