Mossbauer study of ferrite systems Co x Mn1−x Fe2O4 and Ni x Mn1−x Fe2O4

Mössbauer spectra of Co _x Mn_1?x Fe₂O₄ and Ni _x Mn_1?x Fe₂O₄ ferrites withx values ranging from 0·1 to 0·8 in steps of 0·1 have been recorded at room temperature. All spectra exhibit well-defined Zeeman hyperfine patterns. It has been observed that hyperfine field at Fe³⁺ nucleus increases more rapidly by nickel substitution than by cobalt substitution. This has been explained in terms of exchange interactions and cation distribution in the spinels. Hyperfine fields, isomer shifts and quadrupole splittings have been determined.     

Empirical bounds for ruin probabilities

We consider the classical model for an insurance business where the claims occur according to a Poisson process and where the distribution for the cost of each claim fulfills Cramér's tail-condition. Under these conditions Lundberg's constant R is of fundamental importance for ruin calculations.We derive estimates of R, based on an observation of the insurance business and investigate the statistical properties of those estimates. We further derive bounds and confidence intervals for ruin probabilities.     

船舶碰撞危险度模型的构建

运用模糊数学的综合评判理论,把会遇中目标船的DCPA、TCPA两船距离、相对方位、船速比5个因素作为基本评判参数,建立碰撞危险度的评价模型．而将其它因素,如航行区域状况、能见度情况和船舶的操纵性能等,作为对上述因素的危险隶属度函数的修正加以考虑．引入了船舶领域、动界等概念,以对来船构成的本船危险度进行客观有效地评价,为安全避碰提供合理依据．     

Non-classical preference models in combinatorial problems: Models and algorithms for graphs

This is a summary of the most important results presented in the authors PhD thesis (Spanjaard 2003). This thesis, written in French, was defended on 16 December 2003 and supervised by Patrice Perny. A copy is available from the author upon request. This thesis deals with the search for preferred solutions in combinatorial optimization problems (and more particularly graph problems). It aims at conciliating preference modelling and algorithmic concerns for decision aiding.Received: March 2004, MSC classification: 91B06, 90C27, 90B40, 16Y60     

Estimation of the Multivariate Normal Precision Matrix under the Entropy Loss

Let X ₁, , X _n (n > p) be a random sample from multivariate normal distribution N _p (, ), where R ^p and is a positive definite matrix, both and being unknown. We consider the problem of estimating the precision matrix ^–1. In this paper it is shown that for the entropy loss, the best lower-triangular affine equivariant minimax estimator of ^–1 is inadmissible and an improved estimator is explicitly constructed. Note that our improved estimator is obtained from the class of lower-triangular scale equivariant estimators.     

Bayesian networks applied to credit scoring

Email: kchang{at}gmu.eduEmail: RobertFung{at}Fairlsaac.comEmail: alan.lucas{at}hotmail.com^¶Email: BobOliver{at}Fairlsaac.com^||Email: NShikaloff{at}Fairlsaac.com The objectives of this paper are to apply the theory and numericalalgorithms of Bayesian networks to risk scoring, and comparethe results with traditional methods for computing scores andposterior predictions of performance variables. Model identification,inference, and prediction of random variables using Bayesiannetworks have been successfully applied in a number of areas,including medical diagnosis, equipment failure, informationretrieval, rare-event prediction, and pattern recognition. Theability to graphically represent conditional dependencies andindependencies among random variables may also be useful incredit scoring. Although several papers have already appearedin the literature which use graphical models for model identification,as far as we know there have been no explicit experimental resultsthat compare a traditionally computed risk score with predictionsbased on Bayesian learning algorithms. In this paper, we examine a database of credit-card applicantsand attempt to ‘learn’ the graphical structure ofthe characteristics or variables that make up the database.We identify representative Bayesian networks in a developmentsample as well as the associated Markov blankets and cliquestructures within the Markov blanket. Once we obtain the structureof the underlying conditional independencies, we are able toestimate the probabilities of each node conditional on its directpredecessor node(s). We then calculate the posterior probabilitiesand scores of a performance variable for the development sample.Finally, we calculate the receiver operating characteristic(ROC) curves and relative profitability of scorecards basedon these identifications. The results of the different modelsand methods are compared with both development and validationsamples. Finally, we report on a statistical entropy calculationthat measures the degree to which cliques identified in theBayesian network are independent of one another.     

单峰偏好下马斯金单调性与联盟防策略的等价性

本文证明了在单峰偏好域上Maskin单调性与防策略条件是等价的,并进一步证明了Maskin单调性与联盟防策略是等价的.从而推广了Muller-Satterthwaite(1977)在无限制强序域上得到的结论.在此基础上,利用Mollin(1980)在单峰偏好域上提出的防策略社会选择函数特征化定理,证明了在单峰偏好域上能够突破Muller-Satterthwaite不可能性定理所预示的消极结论.     

A method for estimating criteria weights from intuitionistic preference relations

An intuitionistic preference relation is a powerful means to express decision makers’information of intuitionistic preference over criteria in the process of multi-criteria decision making. In this paper, we first define the concept of its consistence and give the equivalent interval fuzzy preference relation of it. Then we develop a method for estimating criteria weights from it, and then extend the method to accommodate group decision making based on them And finally, we use some numerical examples to illustrate the feasibility and validity of the developed method.     

复合二项过程风险模型的精细大偏差及有限时间破产概率

讨论基于客户到来的复合二项过程风险模型.在该风险模型中,假设索赔额序列是独立同分布的重尾随机变量序列,不同保单发生实际索赔的概率可以不同,则在索赔额服从ERV的条件下,得到了损失过程的精细大偏差;进一步地,得到了有限时间破产概率的Lundberg极限结果.