Influence diagnostics for the Weibull-Negative-Binomial regression model with cure rate under latent failure causes

In this paper, we propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest follows the Negative Binomial distribution and the time to event follows a Weibull distribution. Indeed, we introduce the Weibull-Negative-Binomial (WNB) distribution, which can be used in order to model survival data when the hazard rate function is increasing, decreasing and some non-monotonous shaped. Another advantage of the proposed model is that it has some distributions commonly used in lifetime analysis as particular cases. Moreover, the proposed model includes as special cases some of the well-know cure rate models discussed in the literature. We consider a frequentist analysis for parameter estimation of a WNB model with cure rate. Then, we derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and present some ways to perform global influence analysis. Finally, the methodology is illustrated on a medical data.     

Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics

We propose an influence diagnostic methodology for linear regression models with stochastic restrictions and errors following elliptically contoured distributions. We study how a perturbation may impact on the mixed estimation procedure of parameters in the model. Normal curvatures and slopes for assessing influence under usual schemes are derived, including perturbations of case-weight, response variable, and explanatory variable. Simulations are conducted to evaluate the performance of the proposed methodology. An example with real-world economy data is presented as an illustration.     

理论观照与实践反思:乡村振兴道路背景下产业融合探究

为从全球性现代化的视野观察中国现代化道路,通过在湖北西部（鄂西南、鄂西北）、渝东南、贵州（六盘水、遵义、黔东北等）等地烟草行业综合体建设进行调查,对城乡融合发展中的产业融合进行综合考察和研究。研究认为,中国的乡村振兴从“战略”提升为“道路”,表明中国式“两条腿走路”的三农现代化道路认知正式成形,乡村振兴道路在本质上讲是“农村就地现代化道路”,以农业为基础的农村就地现代化道路的关键是农村产业的融合发展;走乡村振兴道路,必须坚持政府是“主导”、乡村是“主场”、就地现代化是“主道”、产业融合发展是“主业”、内生发展是“主流”、三农工作队伍是“主体”、城乡等值发展是“主向”,再从土地流转关系、政策法规、主导产业培育、共享经济平台建设等方面,培育和推进乡村振兴中的产业融合工程。     

回流农民农业经营职业化的影响因素

基于在甘肃、湖南和贵州三省的调查数据,运用二元Logistic回归模型,分析了回流农民农业经营决策和新型农民职业化的影响因素。结果表明:回流农民是否从事农业经营和能否成为新型职业农民同时受到个人禀赋、农业信息感知和乡土情结的影响。个人禀赋的影响表现为:教育程度较高和非常健康的回流农民从事农业经营的可能性低;有培训经历和非常健康的回流农民成为新型职业农民的可能性高;农业信息感知的影响表现为:惠农政策感知水平越高,回流农民从事农业经营的可能性越大,成为新型职业农民的可能性也越大;农业风险感知水平越高,回流农民从事农业经营的可能性越低;支农举措感知水平越高,回流农民成为新型职业农民的可能性越大;乡土情结的影响表现为:有土地流入经历的回流农民从事农业经营的可能性更大,爱农情结越深的回流农民越容易成为新型职业农民。建议从改善农业经营金融扶持与农业保险体系、强化农业技术培训、提升农业信息传播效果和激发回流农民乡土情结四个方面入手,吸引更多回流农民从事农业经营,培育更多回流农民成为新型职业农民。     

城投公司债券信用利差影响因素与对策研究

为防范政府债务风险,减少城投债信用违约事件的发生,采用多元线性回归模型,选取2014～2016年新发城投债中7年期公司债为样本,将政府财政及债券等个体因素相关指标作为自变量,以宏观因素指标作为控制变量,分析中国不同行政级别城投债信用利差的影响因素。研究认为,债券个体因素对县、市和省级城投债信用利差均有显著影响,宏观因素的影响随城投公司所属行政级别升高而升高;地方政府财政因素对各行政级别的影响方向相同,由于城投公司资质存在差异,政府财政因素对低行政级别信用利差的影响显著;不同行政级别下,各类因素对信用利差的影响略有不同,城投公司债券发行信用利差与评级情况和发行规模都呈负向关系,系数绝对值随行政级别的升高而降低,企业自身财务因素影响并不显著。地方政府应大力发展经济使城投公司融资成本降低,投资者在投资前利用多种指标估算债券发行信用利差,城投公司也要注意合理设计发债规模,使自身融资成本达到最低,监管机构加强对低行政级别城投公司债券发行的监管和宏观经济方面的政策引导,以此促进解决城投债问题和推动城投债公司合理发行债券。     

内生式发展模式研究综述

自20世纪70年代以来,欧美处于反思工业化与城市化、保护传统文化和生态环境的思潮之下,"内生式发展"作为致力于解决乡村发展问题的一种新模式,对于不发达地区的复兴起到了积极的作用.内生式发展模式以培养地方基于内部的发展能力为目的,强调当地人的开发主体地位以及建立当地基层组织的必要性.基于内生式发展模式的援助项目已在国际、国内取得了一定的成功,对于目前国内的乡村发展具有一定的借鉴意义.     

在社会主义政治文明建设中坚持和完善民族区域自治制度

民族区域自治制度,是我国的一项基本政治制度,是发展社会主义民主、建设社会主义政治文明的重要内容。坚持和完善民族区域自治制度,必须牢固树立科学发展观,推进民族地区经济、社会全面、协调和可持续发展。     

一种求解双目标flow shop排序问题的进化算法

提出一种求解双目标flow shop排序的递进多目标进化算法.算法采用改进的精英复制策略,在实现精英保留的前提下降低了计算复杂性;通过递进进化模式增加群体多样性,改善了算法收敛性;通过群体进化过程中对非劣解集进行竞争型可变邻域启发式搜索,增强了算法局部搜索性能.采用新算法和参照算法NSGA-II对31个标准双目标flow shop算例进行优化.研究结果表明,新算法在所有算例的求解中均获得了优于NSGA-II的非劣解集,验证了算法的有效性.     

Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics

This paper concerns the geometric treatment of graphical models using Bayes linear methods. We introduce Bayes linear separation as a second order generalised conditional independence relation, and Bayes linear graphical models are constructed using this property. A system of interpretive and diagnostic shadings are given, which summarise the analysis over the associated moral graph. Principles of local computation are outlined for the graphical models, and an algorithm for implementing such computation over the junction tree is described. The approach is illustrated with two examples. The first concerns sales forecasting using a multivariate dynamic linear model. The second concerns inference for the error variance matrices of the model for sales, and illustrates the generality of our geometric approach by treating the matrices directly as random objects. The examples are implemented using a freely available set of object-oriented programming tools for Bayes linear local computation and graphical diagnostic display.     

Bayesian nonparametric modelling of the link function in the single-index model using a Bernstein–Dirichlet process prior

This paper proposes the use of the Bernstein–Dirichlet process prior for a new nonparametric approach to estimating the link function in the single-index model (SIM). The Bernstein–Dirichlet process prior has so far mainly been used for nonparametric density estimation. Here we modify this approach to allow for an approximation of the unknown link function. Instead of the usual Gaussian distribution, the error term is assumed to be asymmetric Laplace distributed which increases the flexibility and robustness of the SIM. To automatically identify truly active predictors, spike-and-slab priors are used for Bayesian variable selection. Posterior computations are performed via a Metropolis-Hastings-within-Gibbs sampler using a truncation-based algorithm for stick-breaking priors. We compare the efficiency of the proposed approach with well-established techniques in an extensive simulation study and illustrate its practical performance by an application to nonparametric modelling of the power consumption in a sewage treatment plant.