实验的自变量是图形的离散度参数，因变量是各离散度图形信号的反应时。
The experimental variable was the dispersion of polygons and the dependent variable was the response time of every polygons.
利用离散型随机变量的联合分布矩阵，得到了离散型随机变量独立性的一种判别方法，并用实例给出了一定的应用。
Making use of the joint distribution matrix of discrete random variables, we get a kind of judgement method about the independence of discrete random variables, give its application by example.
对离散变量的析架尺寸优化问题，本文提出了采用多目标规划的思想、将离散变量优化和连续变量优化结合起来的求解方法。
In sizing optimization of truss with discrete variables, joined up optimization of continuous variable and discrete variable, the idea of multi-objections is used.
并且，在优化过程中根据二进制变量的权重系数逐步确定离散变量的取值，实现了离散变量在优化过程中的逐次归整。
According to weight coefficient of binary variable, discrete variables can be gradually determined in optimization process, and their discretization can be realized during iteration successively.
当生命数据是离散的、未删失数据含有打结的和有协变量信息时，离散生存分析模型是适当的选择。
Discrete-time survival model is appropriate as survival data are discrete, tied and some effects for covariates are added.
采用多目标规划的思想，将离散变量优化和连续变量优化结合起来，较好解决了离散变量优化设计时的难点。
Joined up optimization of continuous variable and discrete variable, the difficult was solved by using the idea of multi-objections.
剖析了凡是对离散型随机变量使用边际分析法的。实际上都已改变了原来的离散型前提。
The paper analyses the fact that the original discrete premise is actually changed in the situation that the marginal analytic method is used towards the discrete random variable.
剖析了凡是对离散型随机变量使用边际分析法的。实际上都已改变了原来的离散型前提。
The paper analyses the fact that the original discrete premise is actually changed in the situation that the marginal analytic method is used towards the discrete random variable.
应用推荐