基于最新统计分类标准的数字经济发展水平测度

随着信息技术的发展,数字经济已经成为经济增长的"新引擎"。但由于缺乏权威的产业统计分类标准,学者们一直面临"数字经济研究缺乏数字依据"的尴尬境地。文章基于国家统计局公布并实施的《数字经济及其核心产业统计分类(2021)》中的分类标准,对各省份统计年鉴的数据进行重新整理,利用熵权法构建数字经济发展指数,测度了我国30个省份的数字经济发展水平,分析了各省份数字经济发展的差异以及时空特征。研究发现,2009—2019年我国数字经济产业发展迅猛,各项子产业都取得了长足的进步。相比较而言,数字要素驱动业发展速度略低于其他三个子产业;数字经济发展存在着明显的区域不平衡。东中部地区的数字经济发展状况明显优于西部地区,南方优于北方,而且区域不平衡有持续扩大趋势。     

Rényi entropy of m-generalized order statistics

Abstract

Characterizing relations via Rényi entropy of m-generalized order statistics are considered along with examples and related stochastic orderings. Previous results for common order statistics are included.     

基于犹豫模糊语言信息的前景决策方法

本文首先回顾了模糊信息下前景理论研究的现状，发现犹豫模糊语言这一决策中常见的信息表达形式在前景理论框架中的研究被忽略，同时犹豫模糊环境下的前景决策方法具有一定的应用背景；基于此，本文考虑到决策者在实际决策过程中惯用的信息表达以及面对收益和损失时不同的风险态度，试图在犹豫模糊语言环境下构造新的前景理论决策框架，建立基于犹豫模糊语言信息的前景决策方法，并给出具体的决策步骤；最后通过算例分析展示了该方法的实际应用过程，并与犹豫模糊语言环境下的期望效用决策结果进行对比，说明了该方法更符合实际决策情景。     

网络外部性对双渠道供应链信息分享的影响

研究了网络外部性对双渠道供应链信息分享的影响。分别建立了存在网络外部性和不存在网络外部性下的双渠道供应链模型，通过比较零售商信息分享和不分享下其与制造商的期望利润。研究发现：当未考虑产品的网络外部性时，零售商不与制造商分享其市场需求信息，与已有研究一致。当考虑了产品网络外部性且网络外部性较小时，零售商仍不与制造商分享市场需求信息；然而，当网络外部性较大时，零售商与制造商分享其市场需求信息。此外，零售商与制造商共享其市场需求信息有助于增加制造商和供应链利润。     

Blinded continuous monitoring in clinical trials with recurrent event endpoints

In studies with recurrent event endpoints, misspecified assumptions of event rates or dispersion can lead to underpowered trials or overexposure of patients. Specification of overdispersion is often a particular problem as it is usually not reported in clinical trial publications. Changing event rates over the years have been described for some diseases, adding to the uncertainty in planning. To mitigate the risks of inadequate sample sizes, internal pilot study designs have been proposed with a preference for blinded sample size reestimation procedures, as they generally do not affect the type I error rate and maintain trial integrity. Blinded sample size reestimation procedures are available for trials with recurrent events as endpoints. However, the variance in the reestimated sample size can be considerable in particular with early sample size reviews. Motivated by a randomized controlled trial in paediatric multiple sclerosis, a rare neurological condition in children, we apply the concept of blinded continuous monitoring of information, which is known to reduce the variance in the resulting sample size. Assuming negative binomial distributions for the counts of recurrent relapses, we derive information criteria and propose blinded continuous monitoring procedures. The operating characteristics of these are assessed in Monte Carlo trial simulations demonstrating favourable properties with regard to type I error rate, power, and stopping time, ie, sample size.     

Accurate computation of single and product moments of order statistics under progressive censoring

An accurate procedure is proposed to calculate approximate moments of progressive order statistics in the context of statistical inference for lifetime models. The study analyses the performance of power series expansion to approximate the moments for location and scale distributions with high precision and smaller deviations with respect to the exact values. A comparative analysis between exact and approximate methods is shown using some tables and figures. The different approximations are applied in two situations. First, we consider the problem of computing the large sample variance–covariance matrix of maximum likelihood estimators. We also use the approximations to obtain progressively censored sampling plans for log-normal distributed data. These problems illustrate that the presented procedure is highly useful to compute the moments with precision for numerous censoring patterns and, in many cases, is the only valid method because the exact calculation may not be applicable.     

为合法经营活动而侵犯公民个人信息的刑法规制

最高人民法院、最高人民检察院《关于办理侵犯公民个人信息刑事案件适用法律若干问题的解释》第六条对为合法经营活动而侵犯公民个人信息行为进行独立规制,是新型犯罪罪状表述抽象化与罪状解释具体化、信息时代信息价值多元化与危害行为多样化、现代社会犯罪治理精细化与刑法评价精准化的内在要求.为合法经营活动而侵犯公民个人信息行为相关规范要素中的“为合法经营活动”应理解为主观超过要素,“获利五万元”应作严格解释,“曾因侵犯公民个人信息”应作广义解释,“其他情节严重”应包括信息数量标准.     

基于Petri网的微博网络信息传播模型

微博网络中的信息传播模型是分析用户行为，找出传播路径，确定领袖人物，发现舆情热点等研究的基础。虽然多种不同角度的信息传播模型已经得到广泛研究，但缺乏对信息动态传播过程的直观描述。本文基于Petri网的结构和特征，针对微博网络信息传播过程，提出了一种简单直观的描述模型，该模型首先对微博网络的信息动态传播过程中的对象进行结构化描述。本文根据微博网络的用户结构关系，并利用Petri网的相关理论，形式化解释和定义信息传播基本对象，从而更加直接描述了微博网络中的转发、评论、回复等多种用户行为。在此基础上，本文利用Petri网能够描述信息流动问题的特征，结合颜色Petri网和时延Petri网，从Petri网系统的角度表示信息动态传播路径，并研究网络的动态性质和传播条件，使得信息传播模型更加真实地模拟信息传播情况。最后本文分析信息传播算例和新浪微博真实数据实验，验证了模型的有效性和可行性，为舆情态势分析以及用户行为的研究提供帮助和支持，同时也为其它社交网络信息传播的用户行为描述提供了新的思路。     

Price bias and common practice in option pricing

Generally, the semiclosed-form option pricing formula for complex financial models depends on unobservable factors such as stochastic volatility and jump intensity. A popular practice is to use an estimate of these latent factors to compute the option price. However, in many situations this plug-and-play approximation does not yield the appropriate price. This article examines this bias and quantifies its impacts. We decompose the bias into terms that are related to the bias on the unobservable factors and to the precision of their point estimators. The approximated price is found to be highly biased when only the history of the stock price is used to recover the latent states. This bias is corrected when option prices are added to the sample used to recover the states' best estimate. We also show numerically that such a bias is propagated on calibrated parameters, leading to erroneous values. The Canadian Journal of Statistics 48: 8–35; 2020 © 2019 Statistical Society of Canada     

Confidence intervals,significance values,maximum likelihood estimates,etc. sharpened into Occam’s razors

Abstract

Confidence sets, p values, maximum likelihood estimates, and other results of non-Bayesian statistical methods may be adjusted to favor sampling distributions that are simple compared to others in the parametric family. The adjustments are derived from a prior likelihood function previously used to adjust posterior distributions.