组合预测误差信息矩阵研究

研究组合预测误差信息矩阵的结构与组合预测方法性质之间的联系,首次提出冗余信息概念,对最优组合预测方法的组合结构进行了研究。     

《金融会计》教学必须走出的几个误区

《金融会计》课程的教学与近几年来金融业迅猛发展的趋势不相适应 ,在认识上、教学内容上和教学手段等方面存在种种误区     

我国货币政策失效的原因分析及对策

1997年以来,我国的货币政策在经济增长中起到了一定的作用,但也存在一些失效,主要表现在利率机制、准备金政策、公开市场业务等方面存在缺陷。因此,必须不断完善我国的货币政策,以便更好地为经济增长提供政策指导。     

中国劳动力参与率方面存在的问题

目前我国劳动力参与率方面仍存在的许多问题,如劳动力参与率水平总体较高,其中的女性人口劳动力参与率、青年人口劳动力参与率和老年人口劳动力参与率均尤为高。针对这种情况,可考虑通过大力发展教育事业,提高法定劳动年龄界限来解决。     

Bayesian analysis of elapsed times in continuous‐time Markov chains

The authors consider Bayesian analysis for continuous‐time Markov chain models based on a conditional reference prior. For such models, inference of the elapsed time between chain observations depends heavily on the rate of decay of the prior as the elapsed time increases. Moreover, improper priors on the elapsed time may lead to improper posterior distributions. In addition, an infinitesimal rate matrix also characterizes this class of models. Experts often have good prior knowledge about the parameters of this matrix. The authors show that the use of a proper prior for the rate matrix parameters together with the conditional reference prior for the elapsed time yields a proper posterior distribution. The authors also demonstrate that, when compared to analyses based on priors previously proposed in the literature, a Bayesian analysis on the elapsed time based on the conditional reference prior possesses better frequentist properties. The type of prior thus represents a better default prior choice for estimation software.     

Bonus—Malus模型在银行贷款机制中的应用

将Bonus—MalLis模型应用到银行贷款业务，通过调整银行的Bonus-MalLis贷款利率来减少贷款欺诈行为。主要是建立借款人的银行个人信用体系，通过借款人上阶段的还款利率和表现决定其下阶段还款利率，这样就提供了一种与完全审计机制不同的奖惩机制。在一些简单假设下可证明Bonus—Malus利率将会消除所有欺诈行为，而非仅仅减少欺诈行为。     

析科技翻译论著中汉语语法术语的误用

随着科学技术的发展 ,研究和探讨科技翻译的著作不断问世 ,但是目前有些论述科技英汉、汉英翻译的书籍在使用汉语语法术语方面不够正确。该文从词、句子成分和句的角度分析了汉语语法术语误用的情况。     

BATHTUB-TYPE CURVES IN RELIABILITY AND BEYOND

Finding optimal, or at least good, maintenance and repair policies is crucial in reliability engineering. Likewise, describing life phases of human mortality is important when determining social policy or insurance premiums. In these tasks, one searches for distributions to fit data and then makes inferences about the population(s). In the present paper, we focus on bathtub‐type distributions and provide a view of certain problems, methods and solutions, and a few challenges, that can be encountered in reliability engineering, survival analysis, demography and actuarial science.     

An alternative to model selection in ordinary regression

The weaknesses of established model selection procedures based on hypothesis testing and similar criteria are discussed and an alternative based on synthetic (composite) estimation is proposed. It is developed for the problem of prediction in ordinary regression and its properties are explored by simulations for the simple regression. Extensions to a general setting are described and an example with multiple regression is analysed. Arguments are presented against using a selected model for any inferences.     

Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.