半变系数模型研究美国爱荷华州埃姆斯市的房价问题

近年来房地产业发展迅猛,房价快速走高,对经济发展和社会稳定产生了重大影响,因此房价研究具有重要的社会价值和经济意义.文章通过散点图及其拟合曲线展示不同协变量和响应变量之间的相关关系,提出半变系数模型建模美国埃姆斯市的房价问题.文章采用剖面最小二乘法研究7个协变量:地面以上的居住面积、地面以上的房间总数(不包括卫生间)、卫生间总数、房屋整体建材质量和品质、地下室面积、车库面积、建造年份与埃姆斯市房价之间的回归关系,为房价预测研究作准备.研究结果表明半变系数模型在探索美国爱荷华州埃姆斯市房价方面表现较好.因此,文章提供了一种利用半变系数模型同时学习高维数据线性和交互关系的有效方法.     

State space theory of linear time invariant systems with delays in state,control, and observation variables,I

Part I of this paper studies a coupled mathematical system which provides a good model for important families of linear time-invariant hereditary systems: delay-differential equations, integro-differential equations, Volterra-Stieltjes integral equations, functional differential equations of retarded and neutral types, etc. Appropriate states are constructed and associated semigroups and abstract differential equations are obtained. In Part II we emphasize the structural operator approach as in Delfour and Manitius. Control operators are added to the coupled mathematical system allowing delays in the control variables. Again structural operators are introduced to define the state and obtain abstract differential equations without delays in the control variable as in the work of Vinter and Kwong. Finally observation operators are added which allow for delays in the observation variable and delayed control variables in the observation equation. Again a new state and a state equations are constructed in such a way that no delay appears in the new observation operator thus generalizing the construction of A. Pritchard and D. Salamon.     

A model for housing allocation of a homeless population due to a natural disaster

In the present work we derive and analyze a model considering housing allocation of homeless families due to a natural disaster; we use data from the earthquake of September 1999, in Athens, Greece. We derive a non-linear system of ordinary differential equations and analyze the stability of this system. Also we find an approximate solution of the model for a case study as well as and a numerical solution. Finally we consider possible extensions and improvements of the model making it more realistic.     

Boundary Relations, Unitary Colligations, and Functional Models

Recently a new notion, the so-called boundary relation, has been introduced involving an analytic object, the so-called Weyl family. Weyl families and boundary relations establish a link between the class of Nevanlinna families and unitary relations acting from one Kreĭn space, a basic (state) space, to another Kreĭn space, a parameter space where the Nevanlinna family or Weyl family is acting. Nevanlinna families are a natural generalization of the class of operator-valued Nevanlinna functions and they are closely connected with the class of operator-valued Schur functions. This paper establishes the connection between boundary relations and their Weyl families on the one hand, and unitary colligations and their transfer functions on the other hand. From this connection there are various advances which will benefit the investigations on both sides, including operator theoretic as well as analytic aspects. As one of the main consequences a functional model for Nevanlinna families is obtained from a variant of the functional model of L. de Branges and J. Rovnyak for Schur functions. Here the model space is a reproducing kernel Hilbert space in which multiplication by the independent variable defines a closed simple symmetric operator. This operator gives rise to a boundary relation such that the given Nevanlinna family is realized as the corresponding Weyl family. Received: January 21, 2008., Revised: March 31, 2008.     

住房价格波动对自有住房家庭消费的区域异质性影响研究

为了解决八大类消费品价格数据不易得到的难题,本文构建投入产出价格模型,分别经验研究25个省(自治区和直辖市)住房价格同时变动不同幅度对八大类消费品价格的影响。25个省(自治区和直辖市)消费品价格变动幅度结果即为QUAIDS模型中的消费品价格变量。然后,本文采用CFPS2010数据,在QUAIDS模型中加入反映家庭所在地区的人口特征变量,研究住房价格波动对自有住房家庭消费的区域异质性影响。研究结果表明住房价格波动对自有住房家庭生存型消费需求区域异质性影响的财富效应显著,而对享受型和发展型消费需求区域异质性影响的挤出效应显著。在此基础上,本文进一步运用补偿变动研究住房价格波动对自有住房家庭福利的区域异质性影响。研究结果表明为了提高自有住房家庭的生活质量和促进社会的和谐稳定,政府应该把稳定东部地区住房价格放在首位。且当遇到如何优化家庭消费结构问题时,政府应该根据地区差异划分市场。     

A generalized stochastic goal programming model

In this paper we show how one can get stochastic solutions of Stochastic Multi-objective Problem (SMOP) using goal programming models. In literature it is well known that one can reduce a SMOP to deterministic equivalent problems and reduce the analysis of a stochastic problem to a collection of deterministic problems. The first sections of this paper will be devoted to the introduction of deterministic equivalent problems when the feasible set is a random set and we show how to solve them using goal programming technique. In the second part we try to go more in depth on notion of SMOP solution and we suppose that it has to be a random variable. We will present stochastic goal programming model for finding stochastic solutions of SMOP. Our approach requires more computational time than the one based on deterministic equivalent problems due to the fact that several optimization programs (which depend on the number of experiments to be run) needed to be solved. On the other hand, since in our approach we suppose that a SMOP solution is a random variable, according to the Central Limit Theorem the larger will be the sample size and the more precise will be the estimation of the statistical moments of a SMOP solution. The developed model will be illustrated through numerical examples.     

A stabilized structured Dantzig–Wolfe decomposition method

We discuss an algorithmic scheme, which we call the stabilized structured Dantzig–Wolfe decomposition method, for solving large-scale structured linear programs. It can be applied when the subproblem of the standard Dantzig–Wolfe approach admits an alternative master model amenable to column generation, other than the standard one in which there is a variable for each of the extreme points and extreme rays of the corresponding polyhedron. Stabilization is achieved by the same techniques developed for the standard Dantzig–Wolfe approach and it is equally useful to improve the performance, as shown by computational results obtained on an application to the multicommodity capacitated network design problem.     

A survey of dual-feasible and superadditive functions

Dual-feasible functions are valuable tools that can be used to compute both lower bounds for different combinatorial problems and valid inequalities for integer programs. Several families of functions have been used in the literature. Some of them were defined explicitly, and others not. One of the main objectives of this paper is to survey these functions, and to state results concerning their quality. We clearly identify dominant subsets of functions, i.e. those which may lead to better bounds or stronger cuts. We also describe different frameworks that can be used to create dual-feasible functions. With these frameworks, one can get a dominant function based on other ones. Two new families of dual-feasible functions obtained by applying these methods are proposed in this paper.     

A State Space Model for Software Reliability

In this paper, we propose a non-Gaussion state space model to apply in software reliability. This model assumes an exponential distribution for the failure time in every test-debugging stage, conditionally on the state parameter — the number of faults in the program. It is a generalized JM model which can be applied to the imperfect debugging situation as well as in evolving programs. By examining a set of data on evolving program failures, the effect of evolving program model is amply proved.     

Three enhancements for optimization-based bound tightening

Optimization-based bound tightening (OBBT) is one of the most effective procedures to reduce variable domains of nonconvex mixed-integer nonlinear programs (MINLPs). At the same time it is one of the most expensive bound tightening procedures, since it solves auxiliary linear programs (LPs)—up to twice the number of variables many. The main goal of this paper is to discuss algorithmic techniques for an efficient implementation of OBBT. Most state-of-the-art MINLP solvers apply some restricted version of OBBT and it seems to be common belief that OBBT is beneficial if only one is able to keep its computational cost under control. To this end, we introduce three techniques to increase the efficiency of OBBT: filtering strategies to reduce the number of solved LPs, ordering heuristics to exploit simplex warm starts, and the generation of Lagrangian variable bounds (LVBs). The propagation of LVBs during tree search is a fast approximation to OBBT without the need to solve auxiliary LPs. We conduct extensive computational experiments on MINLPLib2. Our results indicate that OBBT is most beneficial on hard instances, for which we observe a speedup of 17–19 % on average. Most importantly, more instances can be solved when using OBBT.     

Some algorithms for equivalent transformation of nondeterministic finite automata

In this paper we consider algorithms which allow one to combine several states of a nondeterministic finite automaton into one state. Along with the algorithms for combining states, we adduce one more algorithm for the equivalent transformation of a non-deterministic finite automaton, namely, an algorithm for adding cycles. Problems under consideration imply the development of robust computer programs.     

Hamilton-Jacobi theory over time scales and applications to linear-quadratic problems

In this paper we first derive the verification theorem for nonlinear optimal control problems over time scales. That is, we show that the value function is the only solution of the Hamilton-Jacobi equation, in which the minimum is attained at an optimal feedback controller. Applications to the linear-quadratic regulator problem (LQR problem) gives a feedback optimal controller form in terms of the solution of a generalized time scale Riccati equation, and that every optimal solution of the LQR problem must take that form. A connection of the newly obtained Riccati equation with the traditional one is established. Problems with shift in the state variable are also considered. As an important tool for the latter theory we obtain a new formula for the chain rule on time scales. Finally, the corresponding LQR problem with shift in the state variable is analyzed and the results are related to previous ones.     

Duality in disjunctive programming via vector optimization

In this paper, we develop a new duality theory for families of linear programs with an emphasis on disjunctive linear optimization by proposing a vector optimization problem as dual problem. We establish that the well-known relations between primal and dual problems hold in this context. We show that our method generalizes the duality results of Borwein on families of linear programs, of Balas on disjunctive programs, and of Patkar and Stancu-Minasian on disjunctive linear fractional programs. Moreover, we can derive some duality results for integer and for fractional programs where the denominator is not assumed (as usual) to be greater than zero for each feasible point.     

一种估算马尔柯夫状态转移概率矩阵的新方法

在现有文献研究的基础上,对马尔柯夫状态转移概率矩阵估算方法又作了进一步研究,根据马尔柯夫状态转移概率矩阵的性质和特点,提出了一种新的估算方法.方法首先构造了一个以相对误差绝对值之和最小为目标,以某一状态转移到其他状态的概率之和等于1以及状态转移概率不小于零为约束条件的优化模型.在此基础上,通过变量替换,将该模型转化为线性规划模型.由于线性规划模型不仅能够求得解析解,而且有现成的求解软件,因此不但便于问题求解,而且更加方便、可靠.最后进行了示例计算,验证了给出的马尔柯夫状态转移概率矩阵优化算法的可行性和正确性.     

State space theory of linear time-invariant systems with delays in state,control, and observation variables,II

We study a coupled mathematical system which provides a good model for important families of linear time-invariant hereditary systems: delay-differential equations, integrodifferential equations, Volterra-Stieltjes integral equations, functional differential equations of retarded and neutral types, etc. Appropriate states are constructed and associated semigroups and abstract differential equations are obtained. We emphasize the structural operator approach as in Delfour and Manitius. Control operators are added to the coupled mathematical system allowing delays in the control variables. Again structural operators are introduced to define the state and obtain abstract differential equations without delays in the control variable as in the work of Vinter and Kwong. Finally observation operators are added which allow for delays in the observation variable. Again a new state and a state equations are constructed in such a way that no delay appear in the new observation operator as in the recent work of D. Salamon.     

正态总体方差的最短区间估计与最佳双边检验

用传统方法得到的正态总体的方差的置信区间显然不是最短的 ,因而在这个意义上说也不是最佳的 .对从 3到 45的 n及α=0 .2 5 ,0 .2 0 ,0 .1 5 ,0 .1 0 ,0 .0 5 ,0 .0 1 ,0 .0 0 5 ,我们得到了附表一 ,由此可以查出相应的最短置信区间 .同样 ,在对正态总体的方差进行双边检验时 ,传统的方法给出的临界值也不是最佳的 .对如下的 n和 α我们得到了附表二 ,由此可以查出最佳的临界值 .进行计算所需的程序由我们自己编写     

Stability-enhancing control of a coupled transport–diffusion system with Dirichlet actuation and Dirichlet measurement

We investigate the problem of enhancing the stability of a coupled transport–diffusion system with Dirichlet actuation and Dirichlet measurement. In the recent paper [H. Sano, Neumann boundary control of a coupled transport–diffusion system with boundary observation, J. Math. Anal. Appl. 377 (2011) 807–816], we treated the stabilization problem for the case with Neumann actuation and Dirichlet measurement, where the variable transformation of the state is performed by using the fractional power of an unbounded operator. However, we cannot use the similar transformation for the case with Dirichlet actuation and Dirichlet measurement, since it brings an ill-posed expression of the system. So, we use an algebraic approach for the formulation of the system. In this paper, it is shown that a reduced-order model with a finite-dimensional state variable is controllable and observable. The fact enables us to construct a finite-dimensional stability-enhancing controller for the original infinite-dimensional system by using a residual mode filter (RMF) approach. The novelty of this paper is the structure that the controller contains the dynamics with respect to the control variable. As a result, the state vector of the resulting closed-loop system includes the control variable as its entry.     

The bivariate Ising polynomial of a graph

In this paper we discuss the two variable Ising polynomials in a graph theoretical setting. This polynomial has its origin in physics as the partition function of the Ising model with an external field. We prove some basic properties of the Ising polynomial and demonstrate that it encodes a large amount of combinatorial information about a graph. We also give examples which prove that certain properties, such as the chromatic number, are not determined by the Ising polynomial. Finally we prove that there exist large families of non-isomorphic planar triangulations with identical Ising polynomial.     

THE COSTATE VARIABLE IN A STOCHASTIC RENEWABLE RESOURCE MODEL

ABSTRACT. In this paper we discuss the costate variable in a stochastic optimal control model of a renewable natural resource, which we call a fishery. The role of the costate variable in deterministic control models has been discussed extensively in the literature. See for example Lyon [1999], Clark [1990, pp. 102 107] and Arrow and Kurz [1970, pp. 35 37]; however, there is little discussion of this variable for stochastic models, even though thecostate variable has similar roles in the two models. In both models the costate variableis a shadow value of the associated state variable, and as such has the role of rationingthe use of the state variable. In addition, as has been shown in Lyon [1999], in natural resource problems the costate variable can be partitioned into a scarcity effect and a cost effect. We show that this same partitioning can be done in the stochastic renewable resource problem. We discuss and contrast the similarities and differences in these concepts for deterministic and stochastic models. In addition, we present a numerical example to help solidify the results.     

Superconvergence and $L^{\infty}$-Error Estimates of RT1 Mixed Methods for Semilinear Elliptic Control Problems with an Integral Constraint

In this paper, we investigate the superconvergence property and the $L^{\infty}$-error estimates of mixed finite element methods for a semilinear elliptic control problem with an integral constraint. The state and co-state are approximated by the order one Raviart-Thomas mixed finite element space and the control variable is approximated by piecewise constant functions or piecewise linear functions. We derive some superconvergence results for the control variable and the state variables when the control is approximated by piecewise constant functions. Moreover, we derive $L^{\infty}$-error estimates for both the control variable and the state variables when the control is discretized by piecewise linear functions. Finally, some numerical examples are given to demonstrate the theoretical results.