Minimax principle on energy dissipation of incompressible shear flow

The energy dissipation rate is an important concept in the theory of turbulence. Doering-Constantin＇s variational principle characterizes the upper bounds （maxi- mum） of the time-averaged rate of viscous energy dissipation. In the present study, an optimization theoretical point of view was adopted to recast Doering-Constantin＇s formu- lation into a minimax principle for the energy dissipation of an incompressible shear flow. Then, the Kakutani minimax theorem in the game theory is applied to obtain a set of conditions, under which the maximization and the minimization in the minimax principle are commutative. The results explain the spectral constraint of Doering-Constantin, and confirm the equivalence between Doering-Constantin＇s variational principle and Howard- Busse＇s statistical turbulence theory.     

矩阵损失下随机回归系数和参数的线性Minimax估计

对于一般的随机效应线性模型Y=Xβ+ε,这里β和ε分别是p维和n维的随机向量,且E(βε)=(Aa0),Cov(βε)=σ2(V10 0V2),(Vi≥0,i=1,2)我们定义了Sα+Qβ的线性Minimax估计,在一定条件下得到了Sα+Qβ在线性估计类中的Minimax估计,并在几乎处处意义下证明了它的唯一性.     

Local asymptotic normality and asymptotical minimax efficiency of the MLE under random censorship

Here we study the problems of local asymptotic normality of the parametric family of distributions and asymptotic minimax efficient estimators when the observations are subject to right censoring. Local asymptotic normality will be established under some mild regularity conditions. A lower bound for local asymptotic minimax risk is given with respect to a bowl-shaped loss function, and furthermore a necessary and sufficient condition is given in order to achieve this lower bound. Finally, we show that this lower bound can be attained by the maximum likelihood estimator in the censored case and hence it is local asymptotic minimax efficient.     

二次损失下增长曲线模型参数阵的线性Minimax可容许估计

本文在二次损失函数下,给出了增长曲线模型参数阵的线性估计在给定的线性估计类中是Minimax可容许估计的充要条件.     

几个极大极小定理

首先证明了拓扑空间中的两个极大极小定量,定理中对函数所要求的条件是很弱的,作为应用,讨论了强区间空间中的极大极小定理。     

回归分析中的目标函数极小化准则

指出了最小二乘回归分析中存在稳健性不好的问题,讨论了用线性规划法计算回归系数的最小一乘准则和极小极大化准则,通过实例计算得出最小一乘准则误差绝对值小,最大误差最大和极小极大化准则误差绝对值之和最大,最大误差最小的结果,指出在实际应用中可以把三种准则下的计算结果进行比较,从中选出最优回归方程。     

A Counterexample to 0-Diagonal Quasiconcavity in a Minimax Inequality

In this paper, a very simple example shows that, in a n- person nonzero-sum game, the quasiconvexity of the payoff functions is not sufficient to establish the 0-diagonal quasiconcavity in the Fan minimax inequality.     

不等式约束极大极小问题的一个新型模松弛强次可行SQCQP算法

针对带不等式约束的极大极小问题,借鉴一般约束优化问题的模松弛强次可行SQP算法思想,提出了求解不等式约束极大极小问题的一个新型模松弛强次可行SQCQP算法.首先,通过在QCQP子问题中选取合适的罚函数,保证了算法的可行性以及目标函数F(x)的下降性,同时简化QCQP子问题二次约束项参数α_k的选取,可保证算法的可行性和收敛性.其次,算法步长的选取合理简单.最后,在适当的假设条件下证明了算法具有全局收敛性及强收敛性.初步的数值试验结果表明算法是可行有效的.     

H-空间中新的非紧极大极小定理、截口定理及非空交定理

本文在无线性结构Ｈ－空间的框架之下给出一个新的ｖｏｎ Ｎｅｕｍａｎｎ型非紧极大极小定理，并且作为其应用而得到一个新的Ｋｙ Ｆａｎ型截口定理和一个新的非空交定理．结果即使在欧几里得空间中也是全新的     

Necessary and Sufficient Conditions for Minimax Fractional Programming

We establish the necessary and sufficient optimality conditions for a class of nondifferentiable minimax fractional programming problems solving generalized convex functions. Subsequently, we apply the optimality conditions to formulate one parametric dual problem and we prove weak duality, strong duality, and strict converse duality theorems.