A multivariate zero-inflated binomial model for the analysis of correlated proportional data

In this paper, a new multivariate zero-inflated binomial (MZIB) distribution is proposed to analyse the correlated proportional data with excessive zeros. The distributional properties of purposed model are studied. The Fisher scoring algorithm and EM algorithm are given for the computation of estimates of parameters in the proposed MZIB model with/without covariates. The score tests and the likelihood ratio tests are derived for assessing both the zero-inflation and the equality of multiple binomial probabilities in correlated proportional data. A limited simulation study is performed to evaluate the performance of derived EM algorithms for the estimation of parameters in the model with/without covariates and to compare the nominal levels and powers of both score tests and likelihood ratio tests. The whitefly data is used to illustrate the proposed methodologies.     

数字化转型背景下油气开发生产组织新模式探索

智能化是强国战略的必备基础,也是企业转型升级的方向。随着大数据、云计算、人工智能和工业互联网等新兴技术蓬勃兴起,全球石油公司不断通过数字化转型以提高核心竞争力。智能化油气开发生产具有全面感知、自动操控、趋势预测、优化决策的特征。目前,我国油气开发生产数字化转型面临四个困境：各油气田硬件基础设施参差不齐、数据共享与业务协同处于较低水平、传统的油气开发生产模式不适应智能化条件、智能化油气田建设运行尚无统一标准可供借鉴。智能化油气田开发生产组织新模式应以业务协作共享、一体化智能协同为主要特色,积极实现操作巡检维护、开发生产管理、协同研究、经营管理与决策的一体化智能运营。     

电子商务的智能化营销

互联网和电子商务的出现,在信息获得的手段和方法上突破了传统时空观念的限制,在多方面动摇了企业经营和营销理论的根基。同时也改变了企业外部经营和购销的实务操作模式。传统行业的电子商务得到了广泛的应用,积累了大量的数据,在强大的数据库技术和数据挖掘工具的支持下,从海量的数据中挖掘出有用的信息来提高企业经营管理水平已成为热门的课题,为企业实现智能化营销提供了坚实的基础。     

数据挖掘中关联规则的规范化描述

一、引言数据挖掘(Data Mining)是近年来随着人工智能和数据库技术的发展而出现的一门新兴学科。它是从大量的数据中筛选出隐含的、可信的、新颖的、有效的信息的高级处理过程。关联规则(Association Rule)是其中重要的研究课题,是数据挖掘的主要技术之一,也是在无指导学习系统     

Bootstrapping Malmquist Indices for Danish Seiners in the North Sea and Skagerrak

In connection with assessing how an ongoing development in fisheries management may change fishing activity, evaluation of Total Factor Productivity (TFP) change over a period, including efficiency, scale and technology changes, is an important tool. The Malmquist index, based on distance functions evaluated with Data Envelopment Analysis (DEA), is often employed to estimate TFP changes. DEA is generally gaining attention for evaluating efficiency and capacity in fisheries. One main criticism of DEA is that it does not have any statistical foundation, i.e. that it is not possible to make inference about DEA scores or related parameters. The bootstrap method for estimating confidence intervals of deterministic parameters can however be applied to estimate confidence intervals for DEA scores. This method is applied in the present paper for assessing TFP changes between 1987 and 1999 for the fleet of Danish seiners operating in the North Sea and the Skagerrak.     

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。     

Rate efficient estimation of realized Laplace transform of volatility with microstructure noise

In this paper, we consider the problem of estimating the Laplace transform of volatility within a fixed time interval [0,T] using high‐frequency sampling, where we assume that the discretized observations of the latent process are contaminated by microstructure noise. We use the pre‐averaging approach to deal with the effect of microstructure noise. Under the high‐frequency scenario, we obtain a consistent estimator whose convergence rate is , which is known as the optimal convergence rate of the estimation of integrated volatility functionals under the presence of microstructure noise. The related central limit theorem is established. The simulation studies justify the finite‐sample performance of the proposed estimator.     

个人数据损害的类型及其确定

依告知同意原则构建的个人数据保护制度面临着过度收集、擅自披露与滥用等问题的严重挑战。公权保护路径存在监管力度、范围及效力的局限性,而传统侵权法上的损害观念架空了数据主体的私法救济权利。因此,为保障数字经济的健康发展,必须扩张侵权法上损害的含义。法律上可予赔偿的个人数据损害应延及两类新型损害：数据主体遭受次生损害的风险,以及社会分选歧视、数据监控、自动化决策等造成的人格利益减损。在确定具体赔偿数额时,为解决风险与人格利益减损所产生的经济量化与举证责任之困境,《个人信息保护法》应采用知识产权法中广泛适用的法定赔偿制度。     

编辑无意识偏见及其控制

编辑偏见的存在有利有弊。编辑偏见有“有意识”与“无意识”之别。在编辑实践中,诱导编辑无意识偏见的发生因素主要有:认知懒惰或繁忙,非理性决策思维以及直觉信心等。编辑无意识偏见存在影响了编辑对稿件内容的客观评价,但因无意识编辑偏见具有较强的隐蔽性,消除比较困难,编辑必须通过无意识偏见发生前的“有意识”认知、严格落实“三审制”和利用大数据反馈等措施规避无意识偏见发生,以确保稿件价值选择的客观与公正。     

能源价格波动对中国物价水平的潜在与实际影响

目的/意义原油作为重要的工业原料、大宗商品和战略储备物资,其价格波动对全球经济发展具有重大影响,对原油价格进行预测是能源经济领域的热点研究课题。对国际原油价格预测的主要方法进行系统梳理并展望未来研究方向,有助于该研究领域的纵深发展。设计/方法基于295篇国际期刊文献,对国际油价预测的发展阶段、发表期刊、研究机构等进行归纳总结,然后对近二十年油价预测领域的主要研究方法进行系统梳理和分析,最后对油价预测工作进行评述和趋势展望。结论/发现自2008年金融危机后,油价预测研究快速发展,相关文章主要发表于能源经济领域的权威期刊《Energy Economic》。现有油价预测方法主要包括计量模型、机器学习和混合预测模型。展望未来,利用高频日内交易数据,融合计量和机器学习前沿方法,对原油价格进行区间预测或概率密度预测是值得探索的方向,此外还应深化油价预测结果的实际应用价值。