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41.
42.
Framstad N. C. Øksendal B. Sulem A. 《Journal of Optimization Theory and Applications》2004,121(1):77-98
We give a verification theorem by employing Arrow's generalization of the Mangasarian sufficient condition to a general jump diffusion setting and show the connections of adjoint processes to dynamic programming. The result is applied to financial optimization problems. 相似文献
43.
The aim of this paper is to present two different approachs in order to obtain an existence result to the so-called quadrature
surface free boundary problem. The first one requires the shape derivative calculus while the second one depends strongly
on the compatibility condition of the Neumann problem. A necessary and sufficient condition of existences is given in the
radial case. 相似文献
44.
Andrew V. Goldberg Michael D. Grigoriadis Robert E. Tarjan 《Mathematical Programming》1991,50(1-3):277-290
Goldfarb and Hao (1990) have proposed a pivot rule for the primal network simplex algorithm that will solve a maximum flow problem on ann-vertex,m-arc network in at mostnm pivots and O(n
2
m) time. In this paper we describe how to extend the dynamic tree data structure of Sleator and Tarjan (1983, 1985) to reduce the running time of this algorithm to O(nm logn). This bound is less than a logarithmic factor larger than those of the fastest known algorithms for the problem. Our extension of dynamic trees is interesting in its own right and may well have additional applications.Research partially supported by a Presidential Young Investigator Award from the National Science Foundation, Grant No. CCR-8858097, an IBM Faculty Development Award, and AT&T Bell Laboratories.Research partially supported by the Office of Naval Research, Contract No. N00014-87-K-0467.Research partially supported by the National Science Foundation, Grant No. DCR-8605961, and the Office of Naval Research, Contract No. N00014-87-K-0467. 相似文献
45.
This article concerns the existence of global smooth solution for scalar conservation laws with degenerate viscosity in 2-dimensional space. The analysis is based on successive approximation and maximum principle. 相似文献
46.
当分布密度的形式未知时,参数的极大似然估计没有明确的解析表达式,也不能通过设计算法由计算机运算得到。本文我们将从该分布中抽取的样本当作是来自另一个形式已知的分布密度的样本,该已知分布密度的选取依赖于未知的分布密度,但是具有与未知分布相似的边界性质。基于这两个分布族,我们提出了拟极大似然估计的概念,同时,对这种拟极大似然估计的渐近性质进行了讨论。结果表明拟极大拟然估计与极大似然估计有关相同的渐近性质,并且由于拟极大似然估计的获得不依赖于未知分布密度的形式,只与一已知的分布密度有关,使得通过计算机可以实现对其的求解。 相似文献
47.
生长曲线模型中回归系数阵的极大似然估计的精确分布 总被引:2,自引:0,他引:2
对于生长曲线模型,基于理论发展和应用效果的考虑,本文引入了Gauss型误差.在此误差下,本文研究了模型中回归系数阵的极大似然估计的精确分布,求出了此分布的密度和特征函数. 相似文献
48.
Alexander Schuster 《Proceedings of the American Mathematical Society》2006,134(12):3525-3530
It is shown that the formula for the Möbius pseudodistance for the annulus yields better estimates than previously known for the constant in the Bergman space maximum principle.
49.
Yosihiko Ogata 《Annals of the Institute of Statistical Mathematics》1990,42(3):403-433
This paper describes a method for an objective selection of the optimal prior distribution, or for adjusting its hyper-parameter, among the competing priors for a variety of Bayesian models. In order to implement this method, the integration of very high dimensional functions is required to get the normalizing constants of the posterior and even of the prior distribution. The logarithm of the high dimensional integral is reduced to the one-dimensional integration of a cerain function with respect to the scalar parameter over the range of the unit interval. Having decided the prior, the Bayes estimate or the posterior mean is used mainly here in addition to the posterior mode. All of these are based on the simulation of Gibbs distributions such as Metropolis' Monte Carlo algorithm. The improvement of the integration's accuracy is substantial in comparison with the conventional crude Monte Carlo integration. In the present method, we have essentially no practical restrictions in modeling the prior and the likelihood. Illustrative artificial data of the lattice system are given to show the practicability of the present procedure. 相似文献
50.
Quadratically constrained minimum cross-entropy analysis 总被引:3,自引:0,他引:3
Quadratically constrained minimum cross-entropy problem has recently been studied by Zhang and Brockett through an elaborately constructed dual. In this paper, we take a geometric programming approach to analyze this problem. Unlike Zhang and Brockett, we separate the probability constraint from general quadratic constraints and use two simple geometric inequalities to derive its dual problem. Furthermore, by using the dual perturbation method, we directly prove the strong duality theorem and derive a dual-to-primal conversion formula. As a by-product, the perturbation proof gives us insights to develop a computation procedure that avoids dual non-differentiability and allows us to use a general purpose optimizer to find an-optimal solution for the quadratically constrained minimum cross-entropy analysis. 相似文献