Estimation of the intensity function of an inhomogeneous Poisson process with a change‐point

Recent work on point processes includes studying posterior convergence rates of estimating a continuous intensity function. In this article, convergence rates for estimating the intensity function and change‐point are derived for the more general case of a piecewise continuous intensity function. We study the problem of estimating the intensity function of an inhomogeneous Poisson process with a change‐point using non‐parametric Bayesian methods. An Markov Chain Monte Carlo (MCMC) algorithm is proposed to obtain estimates of the intensity function and the change‐point which is illustrated using simulation studies and applications. The Canadian Journal of Statistics 47: 604–618; 2019 © 2019 Statistical Society of Canada     

A general central limit theorem and a subsampling variance estimator for α‐mixing point processes

We establish a central limit theorem for multivariate summary statistics of nonstationary α‐mixing spatial point processes and a subsampling estimator of the covariance matrix of such statistics. The central limit theorem is crucial for establishing asymptotic properties of estimators in statistics for spatial point processes. The covariance matrix subsampling estimator is flexible and model free. It is needed, for example, to construct confidence intervals and ellipsoids based on asymptotic normality of estimators. We also provide a simulation study investigating an application of our results to estimating functions.     

Bayesian inference for stable Lévy–driven stochastic differential equations with high‐frequency data

In this paper, we consider parametric Bayesian inference for stochastic differential equations driven by a pure‐jump stable Lévy process, which is observed at high frequency. In most cases of practical interest, the likelihood function is not available; hence, we use a quasi‐likelihood and place an associated prior on the unknown parameters. It is shown under regularity conditions that there is a Bernstein–von Mises theorem associated to the posterior. We then develop a Markov chain Monte Carlo algorithm for Bayesian inference, and assisted with theoretical results, we show how to scale Metropolis–Hastings proposals when the frequency of the data grows, in order to prevent the acceptance ratio from going to zero in the large data limit. Our algorithm is presented on numerical examples that help verify our theoretical findings.     

The covariance of the backward and forward recurrence times in a renewal process: the stationary case and asymptotics for the ordinary case

In a Poisson process, it is well-known that the forward and backward recurrence times at a given time point t are independent random variables. In a renewal process, although the joint distribution of these quantities is known (asymptotically), it seems that very few results regarding their covariance function exist. In the present paper, we study this covariance and, in particular, we state both necessary and sufficient conditions for it to be positive, zero or negative in terms of reliability classifications and the coefficient of variation of the underlying inter-renewal and the associated equilibrium distribution. Our results apply either for an ordinary renewal process in the steady state or for a stationary process.     

A Bitcoin-inspired infinite-server model with a random fluid limit

The synchronization process inherent to the Bitcoin network gives rise to an infinite-server model with the unusual feature that customers interact. Among the closed-form characteristics that we derive for this model is the busy period distribution which, counterintuitively, does not depend on the arrival rate. We explain this by exploiting the equivalence between two specific service disciplines, which is also used to derive the model’s stationary distribution. Next to these closed-form results, the second major contribution concerns an asymptotic result: a fluid limit in the presence of service delays. Since fluid limits arise under scalings of the law-of-large-numbers type, they are usually deterministic, but in the setting of the model discussed in this paper the fluid limit is random (more specifically, of growth-collapse type).     

论美国保护预备被监护人权益的基本原则

预备被监护人是指即将被安排监护的当事人.经过十余年改革,美国成年监护制度形成了保护预备被监护人权益的一系列基本原则.这些原则包括:"实质性损害"标准、最小限制性替代措施、"功能性行为能力"标准、正当程序原则.我国成年监护制度立法理念相对落后,借鉴美国的成功经验来重构和完善我国的成年监护制度具有重要意义.     

论民族自治县级政府行政执行过程中的监督制约

行政执行是整个行政运行系统的一个重要环节.自治县级政府政策执行必然会受到来自政治系统内外的各种政治与行政权力和社会力量的监督和约束.在现行的体制下,当前自治县级监督机关在人事、财政、福利等方面与执行机关有着密切的利益依附关系,难以有效地对政府行政执行过程进行全方位的监督.为此,有必要通过相关体制的改革和制度安排以建立协调统一、高效灵活的自治县级政府行政执行监督机制,从而更好地对政府执行进行监督与制约.     

流程CIMS项目经济评价方法研究

计算机集成制造系统(CIMS)是一种新型生产管理模式,但由于流程工业企业CIMS工程项目投资大、风险大,开发一种合理评价流程CIMS项目的经济评价方法已是十分必要.文章分析了流程CIMS项目经济评价的特点和各种先进制造技术的评价方法,提出采用效用叠加模型与层次分析法结合起来构成的复合评价方法对流程CIMS项目进行经济评价,并简介了该方法的运用模式,为流程企业实践提供参考.     

高等学校对学生违纪处分之正当程序探索

我国高等学校对学生违纪处分中存在诸多问题,比如没有专门的学生违纪处分主体、不告知学生应当享有的权利等,导致近几年来出现许多学生告学校的案例.采用分析的方法提出,为了减少纠纷的发生,应当完善高校学生管理规定中对学生违纪处分的程序,比如建立事先通知程序、在审理程序中举行听证、规范送达和告知程序等.     

多目标决策的农户小额信贷绩效评价模型研究

近年来,农村信用社投放了大量的农户小额信贷,农户小额信贷对“三农”的影响到底如何？如何评价其综合绩效？文章通过分析并设置了农户小额信贷绩效评价体系,建立了基于层次分析法（AHP）的农户小额信贷综合绩效评价模型,并用此模型对湖北省XC县农村信用社投放的农户小额信贷进行了实例检验。