On the Kolmogorov Inequality for M Φ -Norm

In this paper, we prove the Kolmogorov inequality for M | -norms generated by concave functions (with the same constants as in the Kolmogorov inequality).     

The Inequality Process Versus the Saved Wealth Model: Which Is the More Likely to Imply an Analogue of Thermodynamics in Social Science?

The Inequality Process (IP) and the Saved Wealth Model (SW) are theories of income distribution. The IP's social science metatheory requires its stationary distribution to fit the distribution of labor income conditioned on education. The SW is a modification of the particle system model of the kinetic theory of gases (KTG), the basis of gas thermodynamics. The IP is a particle system similar to the SW and KTG. This article shows that the IP passes the empirical test required of it by social science theory better than the SW. The IP's advantage increases as the U.S. labor force becomes more educated. The IP may the better bet to imply an analogue of thermodynamics in social science.     

Some properties of a generalized Hamy symmetric function and its applications

This paper is concerned with the generalized Hamy symmetric function

     

A Berry-Essen Inequality for the Kaplan-Meier L-Estimator

Let be the Kaplan-Meier estimator of distribution function F. Let J(˙) be a measurable real-valued function. In this paper, a U-statistic representation for the Kaplan-Meier L-estimator, , is derived. Furthermore, the representation is also used to establish a Berry-Essen inequality for . Received September 28, 1998, Accepted March 10, 1999     

An SQP-filter method for inequality constrained optimization and its global convergence

In this paper, we combine the filter technique with a modified sequential quadratic programming (SQP) method. The optimization solution is obtained by reducing step length, which is obtained by an exact linear search. Furthermore, this method can start with an infeasible initial point. The method uses a filter to promote global convergence.     

Error bounds in mathematical programming

Originated from the practical implementation and numerical considerations of iterative methods for solving mathematical programs, the study of error bounds has grown and proliferated in many interesting areas within mathematical programming. This paper gives a comprehensive, state-of-the-art survey of the extensive theory and rich applications of error bounds for inequality and optimization systems and solution sets of equilibrium problems. This work is based on research supported by the U.S. National Science Foundation under grant CCR-9624018.     

具有分布时滞耦合神经网络模型的全局同步性分析

本文研究了具分布时滞的神经网络的全局同步性.通过应用Lyapunov泛函和线性矩阵不等式,获得了关于模型全局同步性的几个判定准则,并通过对相关例子进行了数值的仿真,模拟结果与理论分析吻合.