This method compares two estimators of the marginal distribution of Y (or the joint distribution of (Y, Z)): one is the non-parametric maximum likelihood estimator and the other is an estimator based on the null hypothesis. This method is called the marginal distribution (MD) method or the...
marginal area 边缘地区 marginal credit 边际信贷,限界信贷 相似单词 marginal a. 边缘的,末端的,有旁注的 distribution n. 1.分发,分配 2.散布,分布 3.分配;分布 4.(商品)运销,经销,分销 5.按比例分配;分配法;分发方式 6.分配物,配给物;分发物 7.布置,配置,位置 JOINT 接头,接缝;接合点 joint...
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2) joint probability distribution 联合分布 1. The Gumbel-Hougaard Copula was employed to construct a bivariate joint probability distribution for describing flood peak and flood volume,whose marginal distributions are both the Pearson type Ⅲ. 利用Gumbel-Hougaard Copula构造边缘分布为PⅢ型分布的两...
color: It is the parameter used to take a color for the plot elements. space: It denotes the space between a joint distribution and marginal distribution. xlim, ylim: It represents the limit of the x-axis and y-axis. Example ADVERTISEMENTEarlier, we discussed a joint plot consisting of 3...
2.2 Joint distribution optimal transport loss The main idea of this work is is to handle a change in both marginal and conditional distributions.As such,we are looking for a transformation T that will align directly the joint distributions Ps and Pt.Following the Kantovorich formulation of(2),...
22 4 2 3 1/ 4 2 64 5.Independence of two or more random variables Definition 3.12 Let X and Y be two random variables, discrete or continuous, with joint probability distribution f(x,y) and marginal distribution g(x) and h(y), respectively. The random variable X and Y are said to...
1)joint distribution联合分布 1.The Gumbel-hougaard Copula function was used to analyze the joint distributions between annual maximum daily storm and seven-day storm amounts which are both with Pearson type III marginal distributions.利用Gumbel-Hougaard Copula函数构建边缘分布均为PIII型分布的年最大日雨...
Suppose \pi (\theta _{j}) is the prior distribution of the conditional model p(Y_j|Y_{-j}, \theta _{j}) and \pi (\theta _{-j}) is the prior distribution of the marginal model p(Y_{-j}|\theta _{-j}), then the non-informative margins condition is satisfied if the joint...
independence of x and y f x x f x|y f y y f y|x In words, if the random variables x and y are independent, the conditional distribution for each variable is the same as that variable’s marginal distribution. If x and y are independent, the distribution of x does not depend on...