A residual inaccuracy measure based on the relevation transform

Inaccuracy and information measures based on the cumulative residual entropy are useful in various fields, and are attracting increasing attention in Probability Theory and Statistics. In this paper, we introduce and study an inaccuracy measure concerning the relevation transform of two nonnegative continuous random variables. We investigate various distributional properties and characterization results that are based on the mean residual lifetime and involve the generalized Pareto distribution. A connection with the proportional hazards model is also provided. We obtain comparison results involving the proposed inaccuracy measure and some existing inaccuracy measures. Some illustrative examples are finally given.     

Some results on residual entropy function

Ebrahimi and Pellerey (1995) and Ebrahimi (1996) proposed the Shannon residual entropy function as a useful dynamic measure of uncertainty. They studied the characterization problem from the residual entropy. They also used this function to define a stochastic order and two classes of distributions, DURL and IURL. In this paper, we obtain some new results on this function and we correct some mistakes in the preceding literature.Supported by Ministerio de Ciencia y Tecnologia under grant BFM2000-0362Acknowledgements. We thank two anonymous referees for some useful comments that led to an improvement in the presentation of this paper.     

Probability theory in fuzzy sample spaces

This paper tries to develop a neat and comprehensive probability theory for sample spaces where the events are fuzzy subsets of The investigations are focussed on the discussion how to equip those sample spaces with suitable -algebras and metrics. In the end we can point out a unified concept of random elements in the sample spaces under consideration which is linked with compatible metrics to express random errors. The result is supported by presenting a strong law of large numbers, a central limit theorem and a Glivenko-Cantelli theorem for these kinds of random elements, formulated simultaneously w.r.t. the selected metrics. As a by-product the line of reasoning, which is followed within the paper, enables us to generalize as well as to bring together already known results and concepts from literature.Acknowledgement. The author would like to thank the participants of the 23rd Linz Seminar on Fuzzy Set Theory for the intensive discussion of the paper. Especially he is indebted to Professors Diamond and Höhle whose remarks have helped to get deeper insights into the subject. Additionally, the author is grateful to one anonymous referee for careful reading and valuable proposals which have led to an improvement of the first draft.This paper was presented at the 23rd Linz Seminar on Fuzzy Set Theory, Linz, Austria, February 5–9, 2002.     

Ordering univariate distributions by entropy and variance

This paper examines the role of variance and entropy in ordering distributions and random prospects. There is no universal relation between entropy and variance orderings of distributions. But we place their relationship in the context of a stronger ordering relation known as dispersion ordering. Further, some conditions are identified under which variance and entropy order similarly when continuous variables are transformed. We also analyze parametric changes which do not disturb the agreement between these rankings. The results are conveniently tabulated in terms of distribution parameters.     

Random utility demand models and service location

This paper considers the problem of the optimal location of facilities when the demand behavior is described by a random utility choice model. By means of duality theory of mathematical programming, it is shown how a wide family of such problems can be mapped into an entropy maximizing problem, which is usually easy to solve numerically. Theory and methods are discussed in details for the problem of locating a single type of facilities, and the extension to some kinds of systems with many types of facilities is outlined.     

The entropies: Some roots of ambiguity

Entropy concepts have developed in four general contexts—thermodynamics, communication theory, statistical information theory and social and life sciences. These concepts have five distinct mathematical forms. Ambiguity and complexity in utilization of the concept has been heightened by this multi-faceted heritage. Effective utilization may be strengthened by a sharper articulation of entropy through combinations of literal, mathematical and graphical modes of expression. Geography and planning as user disciplines have important responsibilities in enhancing cross-disciplinary communication of this important adisciplinary concept. Implications of these arguments for the social sciences include the need for caution in drawing social analogies from the ambiguous entropy concepts of statistical mechanics; and an indication of the potential benefits of social science models based on the unambiguous entropic constructs of statistical information theory.     

Modeling and simulation of the quality’s entropy

The aim of the present study is to define quality entropy as well as to illustrate some of its properties. The simulation of the mathematical model for quality entropy shall be performed by means of specialized software for mathematical problem simulation, such as Microsoft Excel that we have employed for this particular study. Our aim is to prove that quality entropy may be expanded to the notions of Markov source of quality and Bernoulli source of quality, by analogy with the Markov and Bernoulli sources employed in information theory. Likewise, the present study delineates some aspects regarding tolerance to quality entropy. The subject of entropy and its application of the management of quality has been approached by other authors as well (Dinu and Vod?, Revista Calitatea-acces la succes, anul 8(4): 60–61, 2007; Dinu, Revista Calitatea-acces la succes, anul 8(5): 62–63, 2007; Georgescu-Roegen, Legea Entropiei ?i Procesul Economic, 1979; Stamatiu, Proceedings of the 7th International Conference on Quality, Reability and Maintainabilty, 2000; Stamatiu, Proceeding of the 18th International Conference on Quality, Reliability and Maintainability, 2002). Through our transdisciplinary approach, we would like to contribute to the development of this subject.     

Consistency of assessments in infinite signaling games

In this paper we investigate possible ways to define consistency of assessments in infinite signaling games, i.e. signaling games in which the sets of types, messages and answers are complete, separable metric spaces. Roughly speaking, a consistency concept is called appropriate if it implies Bayesian consistency and copies the original idea of consistency in finite extensive form games as introduced by ^{Kreps and Wilson (Econometrica 1982, 50, 863–894)}. We present a particular appropriate consistency concept, which we call strong consistency and give a characterization of strongly consistent assessments. It turns out that all appropriate consistency concepts are refinements of strong consistency. Finally, we define and characterize structurally consistent assessments in infinite signaling games.     

An Updated Literature Review of Distance Correlation and Its Applications to Time Series

The concept of distance covariance/correlation was introduced recently to characterise dependence among vectors of random variables. We review some statistical aspects of distance covariance/correlation function, and we demonstrate its applicability to time series analysis. We will see that the auto‐distance covariance/correlation function is able to identify non‐linear relationships and can be employed for testing the i.i.d. hypothesis. Comparisons with other measures of dependence are included.     

INFORMATION THEORETIC APPROACHES IN ECONOMICS

Economics has seen a recent rise in interest in information theory as an alternative framework to the conventional notion of equilibrium as a fixed state, such as Walrasian market‐clearing general equilibrium. The information theoretic approach is predicated on the notion of statistical equilibrium (SE) that takes a distribution over all possible states as an equilibrium, and therefore predicts the endogenous fluctuations of the system along with its central tendency simultaneously. For this reason, SE approaches can explain the observed data without relying on arbitrary assumptions about random noise and provide useful insights for many interesting economic problems that conventional methods have not been able to satisfactorily deal with. In this paper, we review the key elements of information theory focusing on the notions and applications of entropy and SE in economics, particularly paying attention to how entropy concepts open up a new frontline of economic research.     

On Social Statement Spaces

In this fundamental draft we shall introduce the concept of social propositional spaces as a general notion of social science and in particular language, logic and methodology. This should help us bridge an old gap between extension and cognition, or said in more specific words, between space as conceived in mathematics or physics and space as is brought in by social location, by the meaning of predicates, their explanation and logic. ¹ We shall not rely on the idea of factor analysis where some “main components” are fit into the data. Because the notion of euclidean normalization and orthogonality, in this context, is a bit artificial. We first show how combinatorial manifolds of statements can be represented in finite vector spaces over the Galois field F₂. This space which we denote as logic statement space can be spanned by generators of alternating codes. In this way the old concepts of truth tables and interaction attributes can be linked to informatics and in particular code theory and geometry. Extending the logic statement space onto a real vector space by mapping units of the finite rings onto units of the real rings we obtain logistic statement spaces. It turns out that vectors in logistic statement spaces represent cross-tables of logits connected with logistic regression analysis. As a completion of the theory we show that the logit is the first derivative of entropy with respect to probability.     

Neyman–Pearson Lemma for Fuzzy Hypotheses Testing with Vague Data

In hypotheses testing, such as other statistical problems, we may confront imprecise concepts. One case is a situation in which both hypotheses and observations are imprecise. This paper tries to develop a new approach for testing fuzzy hypothesis when the available data are fuzzy, too. First, some definitions are provided, such as: fuzzy sample space, fuzzy-valued random sample, and fuzzy-valued random variable. Then, the problem of fuzzy hypothesis testing with vague data is formulated. Finally, we state and prove a generalized Neyman–Pearson Lemma for such problem. The proposed approach is illustrated by some numerical examples.     

Missing Data: A Unified Taxonomy Guided by Conditional Independence

Recent work (Seaman et al., 2013 ; Mealli & Rubin, 2015 ) attempts to clarify the not always well‐understood difference between realised and everywhere definitions of missing at random (MAR) and missing completely at random. Another branch of the literature (Mohan et al., 2013 ; Pearl & Mohan, 2013 ) exploits always‐observed covariates to give variable‐based definitions of MAR and missing completely at random. In this paper, we develop a unified taxonomy encompassing all approaches. In this taxonomy, the new concept of ‘complementary MAR’ is introduced, and its relationship with the concept of data observed at random is discussed. All relationships among these definitions are analysed and represented graphically. Conditional independence, both at the random variable and at the event level, is the formal language we adopt to connect all these definitions. Our paper covers both the univariate and the multivariate case, where attention is paid to monotone missingness and to the concept of sequential MAR. Specifically, for monotone missingness, we propose a sequential MAR definition that might be more appropriate than both everywhere and variable‐based MAR to model dropout in certain contexts.     

Alcune proprietà strutturali delle reti di Petri

Dopo aver richiamato i concetti fondamentali sulle reti di Petri, si espongono alcune considerazioni sul problema della raggiungibilità ambientato nello spazio delle transizioni. Si introducono quindi alcune nozioni sulla stabilità e limitatezza strutturali delle reti di Petri, che vengono illustrate con un'applicazione a reti di divisori di frequenza binari. Il problema di decidere della stabilità o limitatezza di una rete di Petri è ricondotto a un problema di programmazione lineare.

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After recalling the basic concepts about Petri nets, we consider some aspects of the reachability problem in transition space. In particular, some theorems are given on the markings which enable given firing sequences.The new concept of stability of a Petri net is then introduced and we show that it is possible to decide efficiently if a net is stable or bounded by solving a unique linear programming problem.An application to binary frequency divisors is given last.

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Lavoro eseguito nell'ambito del Progetto CP dell'Università degli Studi di Milano e dell'Honeywell Information Systems Italia, e del programma di ricerca finanziato dal C.N.R., contratto n. 79.00701.02.     

高中数学基本概念教学研究——浅谈高中新课程的数学基本概念的教学

概念教学是课堂教学的组成部分,在中学数学教学中占有很重要位置。为了促进中学数学概念教学质量的提高,要切实搞好新课程数学概念教学的以下几个方面研究:(1)充分挖掘数学概念产生的知识背景,让学生在体验概念产生过程中学习数学概念;(2)重视问题性;(3)重视创设体现数学概念的思想方法的情境;(4)注重概念联系性;(5)注重应用性。     

Cloud manufacturing: from concept to practice

The concept of cloud manufacturing is emerging as a new promising manufacturing paradigm, as well as a business model, which is reshaping the service-oriented, highly collaborative, knowledge-intensive and eco-efficient manufacturing industry. However, the basic concepts about cloud manufacturing are still in discussion. Both academia and industry will need to have a commonly accepted definition of cloud manufacturing, as well as further guidance and recommendations on how to develop and implement cloud manufacturing. In this paper, we review some of the research work and clarify some fundamental terminologies in this field. Further, we developed a cloud manufacturing systems which may serve as an application example. From a systematic and practical perspective, the key requirements of cloud manufacturing platforms are investigated, and then we propose a cloud manufacturing platform prototype, MfgCloud. Finally, a public cloud manufacturing system for small- and medium-sized enterprises (SME) is presented. This paper presents a new perspective for cloud manufacturing, as well as a cloud-to-ground solution. The integrated solution proposed in this paper, including the terminology, MfgCloud, and applications, can push forward this new paradigm from concept to practice.     

Fuzzy grey relation method for multiple criteria decision-making problems

Combining the concepts of fuzzy set theory, entropy, ideal, and grey relation analysis, a fuzzy grey relation method for multiple criteria decision-making problems is proposed. First, triangular fuzzy numbers and linguistic values characterized by triangular fuzzy numbers are used to evaluate the importance weights of all criteria and the superiority of all alternatives versus various criteria above the alternative level. Then, the concept of entropy is utilized to solve the adjusted integration weight of all objective criteria above the alternative level. Furthermore, using the concepts of ideal, the grey ration grades of various alternatives versus ideal solution are ranked to determine the best alternative. Finally, a numerical example of selecting most appropriate company to build a new highway is used to demonstrate the applicability of proposed method. The study results show that this method is an effective means for tackling MCDM problems in fuzzy and grey environments.     

Information in generalized method of moments estimation and entropy-based moment selection

In this paper, we make five contributions to the literature on information and entropy in generalized method of moments (GMM) estimation. First, we introduce the concept of the long run canonical correlations (LRCCs) between the true score vector and the moment function f(_vt,_θ0)$f(v_t,{\theta }_0)$ and show that they provide a metric for the information contained in the population moment condition E[f(_vt,_θ0)]=0$\mathrm{E}[f(v_t,{\theta }_0)]=0$. Second, we show that the entropy of the limiting distribution of the GMM estimator can be written in terms of these LRCCs. Third, motivated by the above results, we introduce an information criterion based on this entropy that can be used as a basis for moment selection. Fourth, we introduce the concept of nearly redundant moment conditions and use it to explore the connection between redundancy and weak identification. Fifth, we analyse the behaviour of the aforementioned entropy-based moment selection method in two scenarios of interest; these scenarios are: (i) nonlinear dynamic models where the parameter vector is identified by all the combinations of moment conditions considered; (ii) linear static models where the parameter vector may be weakly identified for some of the combinations considered. The first of these contributions rests on a generalized information equality that is proved in the paper, and may be of interest in its own right.     

Individual rights and organizational theory

Rights are very important concepts in everyday life. And they are especially important to participants in organizations. Yet, our theories of organization and management have largely ignored rights — stressing, instead, other concepts, such as goals, roles, etc. This article describes the historical significance of rights and their relevance in understanding social behavior. The advantages of a right-based organizational theory (versus traditional goal-based theories) are discussed.This article draws on the author's forthcoming book,A Social-Contract Theory of Organizations (University of Notre Dame Press, 1988).     

Mean residual life functions of finite mixtures,order statistics and coherent systems

We study properties of the mean residual life functions of finite mixtures. Specifically, we study ordering properties, monotonicity and the limiting behaviour. We show, under some mild conditions, that the limiting behaviour is similar to that of the strongest member (in the mean residual life order) of the mixture. We also consider the case of negative mixtures (i.e., mixtures with some negative coefficients) which is applied to study the behaviour of the mean residual life of order statistics and coherent systems with possibly dependent components. Partially Supported by Ministerio de Ciencia y Tecnologí a under grant BFM2003-02947 and Fundación Séneca under grant 00698/PI/04.