A Numerical Solution to the Nonhomogeneous Two-Stage MVK Model of Cancer

In this article, we describe a straightforward method for solving the probability of at least one malignant cell by time t, and the associated hazard function, in the general (i.e., nonhomogeneous) two-stage Moolgavkar-Venzon-Knudson (MVK) model of cancer. The method consists of solving four coupled ordinary differential equations derived from the Kolmogorov backward equations for this process. The relationship of this method to previously proposed solutions is discussed.     

On the preservation of copula structure under truncation

The author characterizes the copula associated with the bivariate survival model of Clayton (1978) as the only absolutely continuous copula that is preserved under bivariate truncation.     

Seasonal forcing on the dynamics ofClethrionomys rufocanus: Modeling geographic gradients in population dynamics

We interpret gradients in population dynamics of the gray-sided vole from the southwestern part of the island of Hokkaido to its northeastern part within the framework of a phenomenological model involving the relative length of summer and winter. In Hokkaido, as in other northern regions, both spring and fall is considered as short transition periods between the two main seasons — summer (the primary breeding season) and winter (the non-reproductive or secondary breeding season). We show that the geographic transition in dynamics may be understood as the combined consequence of different patterns of density-dependence during summer and winter, and geographically varying season lengths. Differences are shown to exist between summer and winter with respect to strength of density-dependence. Direct density-dependence, in particular, is stronger during winter than during summer. A model is presented to show how relative lengths of seasons can induce both stable and periodically fluctuating population dynamics. The results are compared and contrasted with what is otherwise known about the gradient in rodent dynamics in Fennoscandia.     

A new heteroscedastic regression to analyze mass loss of wood in civil construction in Brazil

A heteroscedastic regression based on the odd log-logistic Marshall–Olkin normal (OLLMON) distribution is defined by extending previous models. Some structural properties of this distribution are presented. The estimation of the parameters is addressed by maximum likelihood. For different parameter settings, sample sizes and some scenarios, various simulations investigate the performance of the heteroscedastic OLLMON regression. We use residual analysis to detect influential observations and to check the model assumptions. The new regression explains the mass loss of different wood species in civil construction in Brazil.     

民营科技企业创新服务体系研究

民营科技企业创新服务体系是指民营科技企业提供社会化、专业化服务以支撑、促进创新活动和提高创新效率的服务网络。近几年来,我国民营科技企业的创新服务体系随着改革开放的发展得到日益加强,但由于民营科技企业自身的特点也存在许多困难,表现为服务体系模式不明确、中介服务功能单一、创新服务网络化协作较弱、立法管理相对滞后。因此,必须大力规范和发展民营科技企业的创新服务机构,加强和完善创新服务体系,以推动民营科技企业的创新能力。     

A simple two-step procedure using the Fellegi–Sunter model for frequency-based record linkage

The widely used Fellegi–Sunter model for probabilistic record linkage does not leverage information contained in field values and consequently leads to identical classification of match status regardless of whether records agree on rare or common values. Since agreement on rare values is less likely to occur by chance than agreement on common values, records agreeing on rare values are more likely to be matches. Existing frequency-based methods typically rely on knowledge of error probabilities associated with field values and frequencies of agreed field values among matches, often derived using prior studies or training data. When such information is unavailable, applications of these methods are challenging. In this paper, we propose a simple two-step procedure for frequency-based matching using the Fellegi–Sunter framework to overcome these challenges. Matching weights are adjusted based on frequency distributions of the agreed field values among matches and non-matches, estimated by the Fellegi–Sunter model without relying on prior studies or training data. Through a real-world application and simulation, our method is found to produce comparable or better performance than the unadjusted method. Furthermore, frequency-based matching provides greater improvement in matching accuracy when using poorly discriminating fields with diminished benefit as the discriminating power of matching fields increases.     

基于时变参数Copula的ΔCoVaR度量技术

采用基于时变参数Copula的ΔCoVaR度量方法,以动态参数Copula模型描述金融变量间的相依结构、以GARCH类模型描述各金融变量的边际分布,通过构建的联合分布计算ΔCoVaR。利用此方法度量中国大陆与美国、香港的股票市场间的极端风险溢出。实证结果表明:通过此方法计算的ΔCoVaR能同时反映时变波动性与时变相依性,可更灵敏准确地度量危机时的极端风险溢出。     

农村居民消费对我国经济增长影响分析

本文通过建立面板数据模型测度了农村居民消费对我国经济增长的影响效应,认为农村居民消费对我国经济增长具有正向促进作用但不够明显,分析了扩大农村居民消费需求促进经济增长所面临的障碍因素并提出了相应的对策建议。     

三支决策模型及其研究现状分析

目的/意义二分类群体决策问题广泛存在于社会民生和区域经济中的各个领域,例如：公务员面试、酒店推荐以及交通出行路线选择等。因此,需要提出合理的二分类群体决策方法,从而为政府和相关企业提供决策支持。设计/方法在考虑个体后悔规避行为的基础上,建立二分类选择过程,获得个体和群体关于备选方案的二分类向量;进一步建立二分类共识过程,协助个体调整偏好,从而获得具有较高共识水平的二分类。结论/发现从最小调整成本视角,建立了后悔规避行为下二分类群体决策方法,更加贴近现实决策情景,进一步丰富了群体决策方法的应用范围。     

On the Need for Restricting the Probabilistic Analysis in Risk Assessments to Variability

It is common perspective in risk analysis that there are two kinds of uncertainties: i) variability as resulting from heterogeneity and stochasticity (aleatory uncertainty) and ii) partial ignorance or epistemic uncertainties resulting from systematic measurement error and lack of knowledge. Probability theory is recognized as the proper tool for treating the aleatory uncertainties, but there are different views on what is the best approach for describing partial ignorance and epistemic uncertainties. Subjective probabilities are often used for representing this type of ignorance and uncertainties, but several alternative approaches have been suggested, including interval analysis, probability bound analysis, and bounds based on evidence theory. It is argued that probability theory generates too precise results when the background knowledge of the probabilities is poor. In this article, we look more closely into this issue. We argue that this critique of probability theory is based on a conception of risk assessment being a tool to objectively report on the true risk and variabilities. If risk assessment is seen instead as a method for describing the analysts’ (and possibly other stakeholders’) uncertainties about unknown quantities, the alternative approaches (such as the interval analysis) often fail in providing the necessary decision support.