Prediction with a Generalized Cost of Error Function

Classical prediction theory limits itself to quadratic cost functions, and hence least-square predictors. However, the cost functions that arise in practice in economics and management situations are not likely to be quadratic in form, and frequently will be non-symmetric. It is the object of this paper to throw light on prediction in such situations and to suggest some practical implications. It is suggested that a useful, although sub-optimal, manner of taking into account generalized cost functions is to add a constant bias term to the predictor. Two theorems are proved showing that under fairly general conditions the bias term can be taken to be zero when one uses a symmetric cost function. If the cost function is a non-symmetric linear function, an expression for the bias can be simply obtained.     

基于非对称损失函数的过程均值与标准差优化设计

质量特性的过程均值与过程标准差的选定是一个重要的命题,它们是影响质量成本的重要因素.由顾客定义的特性目标均值以及初始标准差往往并不一定能使得总体的质量损失最小化。针对此问题,本文首先讨论了非对称的质量损失函数,并在此基础上构造出质量特性目标均值与标准差的优选模型,进而得到最优目标过程均值与标准差。在模型的应用中表明:其他情况不变的情况下,质量特性最优均值与最优标准差对质量损失系数具有一定的稳健性。     

具有重尾或异方差误差的双变量预测回归模型的中位无偏估计

In this paper, we consider median unbiased estimation of bivariate predictive regression models with non-normal, heavy-tailed or heterescedastic errors. We construct confidence intervals and median unbiased estimator for the parameter of interest. We show that the proposed estimator has better predictive potential than the usual least squares estimator via simulation. An empirical application to finance is given. And a possible extension of the estimation procedure to cointegration models is also described.     

Median Unbiased Estimation of Bivariate Predictive Regression Models with Heavy-tailed or Heteroscedastic Errors

In this paper, we consider median unbiased estimation of bivariate predictive regression models with non-normal, heavy-tailed or heteroscedastic errors. We construct confidence intervals and median unbiased estimator for the parameter of interest. We show that the proposed estimator has better predictive potential than the usual least squares estimator via simulation. An empirical application to finance is given. And a possible extension of the estimation procedure to cointegration models is also described.     

Asymmetric Supply Function Equilibria with Forward Contracts

We consider markets in which firms offer supply functions, rather than a quantity or price alone: the most important examples are wholesale electricity markets. The equilibria in such markets can be hard to characterize. In many cases, whole families of supply function equilibria occur so there are difficulties in determining which equilibrium will be chosen. In this paper, we consider supply function equilibria, when firms hold forward contracts, which is common in electricity markets. Under the assumption that contract positions have been fixed in advance, we characterize the families of supply function equilibria in a duopoly. The existence of forward contracts implies a tightening of the conditions for an equilibrium, and a greater likelihood that no equilibrium solution exists. In the case of three firms, there can be at most one supply function equilibrium, provided that the lowest demand be small enough.     

基于错误系统理论的和式型和向量型错误函数研究

研究了和式型和向量型函数的相关定义及性质,为更好的描述错误系统,以及计算错误值奠定了基础.     

广义Taylor中值函数若干分析性质

文[2-8]对微分中值定理及Taylor定理"中间点"的渐近性质进行了研究,本文在此基础上,给出了"广义Taylor中值函数"的定义,对"广义Taylor中值函数"的分析性质进行了系统的讨论,证明了"广义Taylor中值函数"的单调性、可积性、连续性、可微性等分析性质.     

非对称绝对线性损失下正态总体的参数设计

田口玄一提出了很多损失函数,其中二次损失是应用最为广泛的一种。当实际损失函数不是二次损失函数而使用二次损失时,就会引起参数设计的不正确。在某些情况下,线性损失函数更适合工业应用。本文在非对称的线性损失下,讨论了参数设计的可行性,证明田口先生方法的稳健性设计和灵敏度设计依然行之有效。结果表明性能指标平均值必须稍微偏离目标值,才能使平均损失达到最小。     

Submodular Flow Problem with a Nonseparable Cost Function

Received: February 19, 1996     

促销努力成本信息不对称下供应链回购契约

在由一个供应商和一个销售商构成的二级供应链,假设市场需求受到销售商的促销努力水平的影响,销售季节到来之前,销售商根据促销成本和收益决定最优促销努力水平和订货量。在促销成本不可观测时,利用委托代理理论研究信息不对称时如何通过回购契约揭示真实的促销努力成本。研究结果表明销售商有动机将努力促销成本报高,为了吸引销售商显示真实的促销努力成本,供应商必须付出额外的信息租金,随促销成本增大,销售商通过虚报高成本获得的利润减小,故需要揭示真实成本信息所付出的信息租金随之减小。由于信息租金的付出,导致了非效率现象的产生,使得销售商的最优订货量和促销努力水平均小于完全信息下系统的最优水平,只能得到帕累托改进的次优结果。     

基于非对称损失函数的参数设计

本文针对望目特性的正态指标,在非对称的二次质量损失函数下,讨论了参数设计的可行性, 证明田口方法的稳健性设计和灵敏度设计依然行之有效.定义了调整参数,求出了使质量损失最小的数值解,并给出了参数设计的具体步骤.     

Infinite Time-Dependent Network Equilibria with a Multivalued Cost Function

In this paper, we consider the dynamic traffic network equilibria with possibly an infinite number of routes, a possibly multivalued cost function, and a not necessarily reflexive Banach space of flow trajectories. We investigate the existence of equilibria under a monotonicity assumption on the cost function, as well as an equivalent condition for equilibria under additional constraints. Finally, we give an iterative method for the computation of equilibria. Our results generalize and extend previous results in Refs. 1–2.Communicated by F. GiannessiThe authors are thankful to the referee and Professor F. Giannessi for valuable suggestions and comments leading the paper to its present form.All correspondence should be sent to the first author.     

Generating Signals with Multiscale Time Irreversibility: The Asymmetric Weierstrass Function

Time irreversibility (asymmetry with respect to time reversal) is an important property of many time series derived from processes in nature. Some time series (e.g., healthy heart rate dynamics) demonstrate even more complex, multiscale irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. Several indices to quantify multiscale asymmetry have been introduced. However, there has been no simple generator of model time series with "tunable" multiscale asymmetry to test such indices. We introduce an asymmetric Weierstrass function W(A) (constructed from asymmetric sawtooth functions instead of cosine waves) that can be used to construct time series with any given value of the multiscale asymmetry. We show that multiscale asymmetry appears to be independent of other multiscale complexity indices, such as fractal dimension and multiscale entropy. We further generalize the concept of multiscale asymmetry by introducing time-dependent (local) multiscale asymmetry and provide examples of such time series. The W(A) function combines two essential features of complex fluctuations, namely fractality (self-similarity) and irreversibility (multiscale time asymmetry); moreover, each of these features can be tuned independently. The proposed family of functions can be used to compare and refine multiscale measures of time series asymmetry.     

线性不对称损失时非正态分布过程均值优化

针对常见的两种非正态分布———梯形分布和三角分布,研究线性不对称质量损失时其过程均值的优化问题,建立了梯形分布在五种不同情况下线性不对称质量损失的数学模型,基于以上模型给出了线性不对称质量损失时梯形分布最优过程均值的确定方法;研究三角分布在四种不同情况下线性不对称质量损失的数学模型,并给出了线性不对称质量损失时三角分布最优过程均值的确定方法。最后,用实例验证本过程均值优化模型的有效性。实例表明,应用线性不对称损失函数,适当的改变过程均值,可以有效地降低产品的质量损失,通过调整工艺过程将获得最佳经济效益。     

On an Error Term Related to the r-th Power of the Euler Totient Function

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一个非对称线性风险函数与证券组合投资分析

在分析Jia&D yer的风险-价值理论基础上,给出了一个基于预先给定的目标收益的非对称线性风险函数.该风险函数是低于参考点的离差和高于参考点的离差的加权和,它利用一阶"上偏矩"来修正一阶下偏矩,进一步建立了在此非对称风险函数下的线性规划证券投资组合模型;并证明了该模型与二阶随机占优准则的一致性;最后通过上海证券市场的实际数据验证了该模型的有效性和实用性.     

随机需求下具有不对称信息的闭环供应链的最优差别定价模型

在随机需求条件下建立了由一个制造商和一个零售商所组成的闭环供应链差别定价模型。在制造商成本信息对称和信息不对称情况下,分别讨论了闭环供应链的最优差别定价问题,得到了在不同信息条件下的最优定价组合以及最优的订购量.最后通过数值算例分析了成本信息不对称对两种产品的零售价以及订购量的影响.     

A Predictive Model for the Police Response Function

The expected response time to a call for service (CFS) for a given configuration of police beats is developed. The effect of downtime calls on the response time to a CFS is determined. Consideration is given to both travel time and waiting time. Travel time and service time distributions are isolated. The model is valid for Poisson arrivals and arbitrary service time distributions. A probabilistic assignment policy is determined for each beat. The fraction of incoming calls arriving in beat k answered by unit l is obtained. Pre-emptive priorities are allowed. Application to the Aurora, Illinois, Police Department is shown.     

基于区间意见的非对称最小成本共识决策问题研究

针对已有共识模型大多是基于精确意见且未考虑决策者意见调整方向约束的不足,引入区间型意见,从最优化角度研究了非对称调整成本下的群决策共识模型。首先,基于区间意见构建了非对称最小成本共识模型。其次,考虑到决策者对不同共识水平的实际需求,通过引入软共识测度,提出了基于区间长度的决策者权重分配方法,据此构建了基于区间意见的非对称最小成本软共识模型。最后,通过政府与污染企业之间关于污染减排决策的实例验证了模型的有效性,并进行了灵敏度分析与比较研究。结果表明:(1)同精确值信息相比,区间意见能够缩减共识成本;(2)与对称成本共识模型相比,非对称调整成本的总共识成本不会随着单位调整成本的增加而无限增大。