灰色预测在安全生产中的应用

采用灰色系统理论中的ＧＭ（１，１）模型对矿井的百万吨死亡率进行了预测，并通过残差修正提高了预测的精度。结果表明，该法具有较高的准确性。     

A Simple Linear Regression Approach to Modeling and Forecasting Mortality Rates

Observing that a sequence of negative logarithms of 1‐year survival probabilities displays a linear relationship with the sequence of corresponding terms with a time lag of a certain number of years, we propose a simple linear regression to model and forecast mortality rates. Our model assuming the linearity between two mortality sequences with a time lag each other does not need to formulate the time trends of mortality rates across ages for mortality prediction. Moreover, the parameters of our model for a given age depend on the mortality rates for that age only. Therefore, whether the span of the study ages with the age included is widened or shortened will not affect the results of mortality fitting and forecasting for that age. In the empirical testing, the regression results using the mortality data for the UK, USA and Japan show a satisfactory goodness of fit, which convinces us of the appropriateness of the linear assumption. Empirical illustrations further show that our model's performances of fitting and forecasting mortality rates are quite satisfactory compared with the existing well‐known mortality models. Copyright © 2015 John Wiley & Sons, Ltd.     

死亡率变化对我国寿险产品纯保费影响的定量研究

寿险产品定价是人寿产品开发的核心,其目的在于确定出适当的价格.而寿险产品定价的基础之一就是经验生命表,由于新经验生命表中死亡率明显下降,会对寿险产品保费产生一定的影响.鉴于新旧生命表的区别,利用寿险精算理论,以终身寿险、定期寿险、生存年金、两全保险等基本寿险产品为例,分析了新生命表下它们各自保费的具体变化,最后通过定量分析给出一些结论.     

Forecasting Longevity Gains Using a Seemingly Unrelated Time Series Model

In this paper a multivariate time series model using the seemingly unrelated time series equation (SUTSE) framework is proposed to forecast longevity gains. The proposed model is represented in state space form and uses Kalman filtering to estimate the unobservable components and fixed parameters. We apply the model both to male mortality rates in Portugal and the USA. Our results compare favorably, in terms of mean absolute percentage error, in‐sample and out‐of‐sample, to those obtained by the Lee–Carter method and some of its extensions. Copyright © 2015 John Wiley & Sons, Ltd.     

Avian mortality due to power lines in the Canary Islands with special reference to the steppe-land birds

Biodiversity is being lost worldwide at an increased rate particularly as the result of human activities and infrastructure. Avian mortality through collision with power lines has been an important topic in animal ecology research, but studies of this kind have never been undertaken in the Canary Islands, a volcanic archipelago located near the northwest African coast that has important seabird colonies, several endemic bird species and endemic races of steppe-land birds of conservation concern. During two contrasting periods in 2008 (breeding vs post-breeding), a total of 366 km of power lines were surveyed on this archipelago covering the entire distributional range of the most important steppe-land bird species (i.e. 232 km, Fuerteventura; 134 km, Lanzarote). In all, 310 carcasses representing 23 families and 26 species were detected. We estimated with distance Sampling that 25.5% and 6.3% of individuals of the total population of Houbara bustards, Chlamydotis undulata fuertaventurae, and Eurasian stone curlews, Burhinus oedicnemus insularum, respectively, were killed in a year. We encourage the Canary Islands authorities (Consejería de Medio Ambiente del Gobierno de Canarias) to try to minimize the Houbara bustard collision rate, particularly in the northern plains of Lanzarote (i.e. Jables de Famara), as a means to reduce mortality of this emblematic species in this insular environment.     

A Flexible Functional Form Approach To Mortality Modeling: Do We Need Additional Cohort Dummies?

The increasing amount of attention paid to longevity risk and funding for old age has created the need for precise mortality models and accurate future mortality forecasts. Orthogonal polynomials have been widely used in technical fields and there have also been applications in mortality modeling. In this paper we adopt a flexible functional form approach using two‐dimensional Legendre orthogonal polynomials to fit and forecast mortality rates. Unlike some of the existing mortality models in the literature, the model we propose does not impose any restrictions on the age, time or cohort structure of the data and thus allows for different model designs for different countries' mortality experience. We conduct an empirical study using male mortality data from a range of developed countries and explore the possibility of using age–time effects to capture cohort effects in the underlying mortality data. It is found that, for some countries, cohort dummies still need to be incorporated into the model. Moreover, when comparing the proposed model with well‐known mortality models in the literature, we find that our model provides comparable fitting but with a much smaller number of parameters. Based on 5‐year‐ahead mortality forecasts, it can be concluded that the proposed model improves the overall accuracy of the future mortality projection. Copyright © 2016 John Wiley & Sons, Ltd.     

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality‐forecasting models be associated with real‐world trends in health‐related variables? Does inclusion of health‐related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle‐related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models. Copyright © 2014 John Wiley & Sons, Ltd.     

预测死亡率分布的一个最小叉熵模型

被保人的死亡率分布是确定寿险费率的一个重要依据,而根据其生活的环境、时间预测被保人的死亡率是保险精算研究中的一个热点问题.基于最小叉熵原理,建立了预测被保人死亡率分布的一个模型--最小叉熵模型,该模型以叉熵函数作为目标函数,以被保人的预期寿命作为约束条件,通过最小化叉熵预测被保人的死亡率.以从事特殊职业的被保人为研究对象,通过最小叉熵模型计算了该类人的死亡率.该方法计算简便,具有较好的客观性和实用性,为死亡率预测研究提供了一种有效的新方法.     

硝苯吡啶治疗急性心肌梗塞安全性的对比观察

目的：探讨硝苯吡啶治疗急性心梗塞的疗效。方法：随机将228例AMI分为三组,硝苯吡啶组和硝苯吡啶加β受体阻滞剂组及对照组。结果：硝苯吡啶组102例,死亡11例,死亡率10．72％;硝苯吡啶加β受体阻滞剂组39例,死亡5例,死亡率为12．82％;对照组87例,死亡12例,死亡率为13．79％。结论：三组相比硝苯吡啶组死亡率最低,但无统计学意义,P＞0．05,故我们认为硝苯吡啶10mg,每日三次对国人是有益的。     

栉孔扇贝大规模死亡病原研究进展

上世纪90年代以来,连续爆发的养殖栉孔扇贝大规模死亡事件给我国的扇贝养殖业造成了重大经济损失,本文就近年来国家“973”课题组在该病害的流行病学调查、病原学研究及单抗免疫学检测等方面所取得的主要研究结果进行了较为系统的综述。