1) box discrete distribution
离散界约束分布
1.
In the third section, under the box discrete distribution of random variables, we present three profit-risk robust portfolio models, which are composed of min-max-type optimization problems.
基于WCVaR模型具有复杂的min-max多层优化结构,在随机变量服从离散界约束分布,损失函数为线性函数的假设下,运用对偶理论将复杂的min-max优化模型转化为简单的线性规划,理论上证明了简化后的模型与原模型的同解性。
2) Discrete boundary constraints
离散边界约束
4) Constraint separation
约束分离
5) separable constraints
可分离约束
6) Discrete distribution
离散分布
1.
This paper is devoted to providing an iterative algorithm for computing the maximum likelihood estimators of discrete distributions under an increasing convex order constraint,and the convergence of the algorithm is proved.
给出在增凸序约束下离散分布的极大似然估计量的一种迭代算法,并证明了该算法的收敛性。
2.
Converting the continuous distributions into discrete distributions will decrease a large amount of computation in Monte-Carlo simulation.
如果把风险变量所符合的连续分布转换为离散分布,能够显著减少蒙特卡罗模拟的计算量。
补充资料：离散
分散不能团聚（多指亲属）：家人～。
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