Estimating rating transition probabilites with missing data

In this article we provide a rigorous treatment of one of the central statistical issues of credit risk management. GivenK-1 rating categories, the rating of a corporate bond over a certain horizon may either stay the same or change to one of the remainingK-2 categories; in addition, it is usually the case that the rating of some bonds is withdrawn during the time interval considered in the analysis. When estimating transition probabilities, we have thus to consider aK-th category, called withdrawal, which contains (partially) missing data. We show how maximum likelihood estimation can be performed in this setup; whereas in discrete time our solution gives rigorous support to a solution often used in applications, in continuous time the maximum likelihood estimator of the transition matrix computed by means of the EM algorithm represents a significant improvement over existing methods.     

On Block Updating in Markov Random Field Models for Disease Mapping

Gaussian Markov random field (GMRF) models are commonly used to model spatial correlation in disease mapping applications. For Bayesian inference by MCMC, so far mainly single-site updating algorithms have been considered. However, convergence and mixing properties of such algorithms can be extremely poor due to strong dependencies of parameters in the posterior distribution. In this paper, we propose various block sampling algorithms in order to improve the MCMC performance. The methodology is rather general, allows for non-standard full conditionals, and can be applied in a modular fashion in a large number of different scenarios. For illustration we consider three different applications: two formulations for spatial modelling of a single disease (with and without additional unstructured parameters respectively), and one formulation for the joint analysis of two diseases. The results indicate that the largest benefits are obtained if parameters and the corresponding hyperparameter are updated jointly in one large block. Implementation of such block algorithms is relatively easy using methods for fast sampling of Gaussian Markov random fields ( Rue, 2001 ). By comparison, Monte Carlo estimates based on single-site updating can be rather misleading, even for very long runs. Our results may have wider relevance for efficient MCMC simulation in hierarchical models with Markov random field components.     

关于培养创新型教师的思考

阐述了在知识经济时代培养创新型教师的必要性和紧迫性 ,针对教师队伍存在的问题 ,提出创新型教师必须具备的能力和素质 ,并从我国教育改革的实际出发 ,探索了培养创新型教师的基本途径     

行政即时强制条件论

行政即时强制是行政法的重要制度之一 ,而行政即时强制条件的设定是行政强制制度确立的关键 ,中国宜借鉴德国、日本等国的有关制度 ,以确保行政法治的实现     

定期租船合同下承运人识别问题研究

在海上货物运输中，以定期租船运输货物时，无论是船东，还是承租人都可能成为承运人。如何确定海上货物运输合同责任主体是海事审判实践中亟待解决的一个理论和实际问题。该文系统分析了定期租船合同下承运人识别问题产生的渊源、承运人识别的依据及其方法，在此基础上作者提出了解决定期租船合同下承运人识别问题的初步建议。     

武则天的家世与生年新探

学术界对于武则天的家世生平多有研究 ,但仍有许多问题悬而未决。史实证明 ,武则天并非出于胡族 ;其母亲杨氏亦非出身寒微 ,以往有关她的年龄记载亦有误。据此 ,杨氏的年龄不足以成为武则天出生地的判断依据。而她出生于广元 ,亦非空穴来风之说     

“当/在S还是X的时候”结构新探

本文分为三个部分。第一部分考察"当/在S还是X的时候"的结构和功能;第二部分分析简缩形式"还是X的时候";第三部分探讨常见组合"当/在S还是X的时候,S'就……"的意义与语用特点。最后是本文的小结。     

Child‐Care Usage and Mother‐Infant “Quality Time”

Mothers' time‐use patterns were compared in families in which infants spent more than 30 hours per week in child care (In‐Care group; n= 143) versus 0 hours per week (At‐Home group; n= 183) from birth to 6 months of age. In‐Care group mothers spent about 12 fewer hours per week interacting with their infants, for about 32% less time; fathers of these infants were more involved in caregiving. The groups did not differ in the quality of mother‐infant interaction. In the In‐Care group, quantity of interaction was related to greater separation anxiety and concerns about effects of maternal employment. Time‐use data were not related to child outcomes at 15 months of age. Results suggest that the effect of extensive time spent apart on the quantity and quality of mother‐infant interaction may be smaller than anticipated.     

论近代中国产业革命被窒息的原因--一个必须遵循先进生产力发展要求的历史实例

近代科学技术与民族棉纺织业私人资本结合是东方型产业革命兴起的直接导因.洋务运动使近代中国具备了产业革命兴起的可能性;但由于晚清政府不能代表当时中国先进生产力的发展要求,造成近代中国棉纺织业的发展走的是一条技术与资本相分离的道路,致使近代中国产业革命被窒息.     

Missing data and forecasting in multivariate time series: An application of the common components dynamic linear model

Summary The paper deals with missing data and forecasting problems in multivariate time series making use of the Common Components Dynamic Linear Model (DLMCC), presented in Quintana (1985), and West and Harrison (1989). Some results are presented and discussed: exploiting the correlation between series, estimated by the DLMCC, the paper shows as it is possible to update state vector posterior distributions for the unobserved series. This is realized on the base of the updating of the observed series state vectors, for which the usual Kalman filter equations can be applied. An application concerning some Italian private consumption series provides an example of the model capabilities.