A discrete-time risk model with Poisson ARCH claim-number process

Abstract

In this paper, we propose a discrete-time risk model with the claim number following an integer-valued autoregressive conditional heteroscedasticity (ARCH) process with Poisson deviates. In this model, the current claim number depends on the previous observations. Within this framework, the equation for finding the adjustment coefficient is derived. Numerical studies are also carried out to examine the impact of the Poisson ARCH dependence structure on the ruin probability.     

Eigenvector centrality and structural zeroes and ones: When is a neighbor not a neighbor?

There will be occasions in which a researcher wants to ignore some dyads in the computation of centrality in order to avoid biased or misleading results. This paper presents a principled way of computing eigenvector-like centrality scores when some dyads are not included in the calculations.     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.     

Discriminant coordinates analysis for multivariate functional data

Abstract

One of the basic statistical methods of dimensionality reduction is analysis of discriminant coordinates given by Fisher (1936 Fisher, R. A. 1936. The use of multiple measurements in taxonomic problem. Annals of Eugenics 7 (2):179–88. doi:10.1111/j.1469-1809.1936.tb02137.x.[Crossref] , [Google Scholar]) and Rao (1948). The space of discriminant coordinates is a space convenient for presenting multidimensional data originating from multiple groups and for the use of various classification methods (methods of discriminant analysis). In the present paper, we adapt the classical discriminant coordinates analysis to multivariate functional data. The theory has been applied to analysis of textural properties of apples of six varieties, measured over a period of 180?days, stored in two types of refrigeration chamber.     

网络环境下服务科学与创新管理研究展望

基于网络环境的服务发展与创新已成为经济发展的新引擎。本文在分析网络环境下服务特征基础上，探讨了其对服务科学与创新管理研究的影响。结合我国社会经济发展对现代服务快速增长的需求，本文提炼了服务科学研究的三类基本科学问题，包括服务价值的内涵与度量，服务资源的要素及其价值生成，和服务关系的界定与形成问题；提出了服务与创新管理的四个重要研究领域，即：服务生态系统的形成与演化，服务资源要素的组织与协调，服务的关联与融合和社会服务运作管理问题。在四个重要研究领域的进一步分析中，论文以一个异质数据服务资源的组织与融合为例，描述了服务资源组织与协调的一个具体问题，说明了已有研究方法解决该问题的困难，和未来该问题研究需要关注的重点；另以平台服务中基于价值和关系的服务定价问题为例，说明服务关联与融合研究的挑战及其未来研究的努力方向。     

延安时期党内政治生态建设理论创新及其时代价值

延安时期,中国共产党的领袖们在党内政治生态建设方面进行了大量卓有成效的理论创新,阐明了党内政治生态建设的内在动力、基本规范、重要途径和根本保障。当前,我们党在全面从严治党过程中,严肃党内政治生活,净化党内政治生态,仍需要从延安时期党内政治生态建设历史经验中汲取营养。     

Testing for Serial Independence: Beyond the Portmanteau Approach

Portmanteau tests are typically used to test serial independence even if, by construction, they are generally powerful only in presence of pairwise dependence between lagged variables. In this article, we present a simple statistic defining a new serial independence test, which is able to detect more general forms of dependence. In particular, differently from the Portmanteau tests, the resulting test is powerful also under a dependent process characterized by pairwise independence. A diagram, based on p-values from the proposed test, is introduced to investigate serial dependence. Finally, the effectiveness of the proposal is evaluated in a simulation study and with an application on financial data. Both show that the new test, used in synergy with the existing ones, helps in the identification of the true data-generating process. Supplementary materials for this article are available online.     

Bayesian estimation of reliability using time-to-failure distribution of parametric degradation models

This paper focusses on computing the Bayesian reliability of components whose performance characteristics (degradation – fatigue and cracks) are observed during a specified period of time. Depending upon the nature of degradation data collected, we fit a monotone increasing or decreasing function for the data. Since the components are supposed to have different lifetimes, the rate of degradation is assumed to be a random variable. At a critical level of degradation, the time to failure distribution is obtained. The exponential and power degradation models are studied and exponential density function is assumed for the random variable representing the rate of degradation. The maximum likelihood estimator and Bayesian estimator of the parameter of exponential density function, predictive distribution, hierarchical Bayes approach and robustness of the posterior mean are presented. The Gibbs sampling algorithm is used to obtain the Bayesian estimates of the parameter. Illustrations are provided for the train wheel degradation data.