LAN property for an ergodic Ornstein–Uhlenbeck process with Poisson jumps

In this article, we consider an ergodic Ornstein–Uhlenbeck process with jumps driven by a Brownian motion and a compensated Poisson process, whose drift and diffusion coefficients as well as its jump intensity depend on unknown parameters. Considering the process discretely observed at high frequency, we derive the local asymptotic normality property. To obtain this result, Malliavin calculus and Girsanov’s theorem are applied to write the log-likelihood ratio in terms of sums of conditional expectations, for which a central limit theorem for triangular arrays can be applied.     

A comparison of maximum likelihood and least squares for the estimation of a cumulative distribution

Monte Carlo methods are used to compare the methods of maximum likelihood and least squares to estimate a cumulative distribution function. When the probabilistic model used is correct or nearly correct, the two methods produce similar results with the MLE usually slightly superior When an incorrect model is used, or when the data is contaminated, the least squares technique often gives substantially superior results.     

材料发展对建筑装饰设计影响的研究

由材料发展引发的一系列关于建筑装饰设计创新的概念,其主要的目的就是更好将建筑装饰设计与材料运用结合起来。只有通过建筑装饰材料的更新与发展,才能达到将建筑装饰设计艺术、技术结合起来快速发展的目标。从建筑装饰材料发展的历史入手,分析建筑装饰材料使用现状,结合材料特性、绿色环保、智能材料、节能材料、低碳等角度对未来材料的可能性发展方向及其对建筑装饰设计的影响进行探讨,总结归纳材料发展对建筑装饰设计影响的一般性规律,促进建筑装饰设计文化的发展与繁荣,营造宜居人居环境。     

Nonparametric Bayesian inference for multivariate density functions using Feller priors

Multivariate density estimation plays an important role in investigating the mechanism of high-dimensional data. This article describes a nonparametric Bayesian approach to the estimation of multivariate densities. A general procedure is proposed for constructing Feller priors for multivariate densities and their theoretical properties as nonparametric priors are established. A blocked Gibbs sampling algorithm is devised to sample from the posterior of the multivariate density. A simulation study is conducted to evaluate the performance of the procedure.     

An integrated model based on statistical process control and maintenance for two-stage dependent processes

The close relationship between quality and maintenance of manufacturing systems has contributed to the development of integrated models which use the concept of statistical process control (SPC) and maintenance. This article demonstrates the integration of the Shewhart individual-residual (Z_X ? Z_e) joint control chart and maintenance for two-stage dependent processes by jointly optimizing their policies to minimize the expected total costs associated with quality, maintenance and inspection. To evaluate the effectiveness of the proposed model, two stand-alone models—a maintenance model and an SPC model—are proposed. Then a numerical example is given to illustrate the application of the proposed integrated model. The results show that the integrated model outperforms the two stand-alone models with regard to the expected cost per unit time. Finally, a sensitivity analysis is conducted to develop insights into time parameters and cost parameters that influence the integration efforts.     

企业内部控制的思考

现代企业从事的社会化大生产,具有分工精细、协作广泛的特点。日新月异的科学技术、加速发展的全球一体化进程,使得企业面临着错综复杂的政治、经济、文化、社会等内部环境。因此,企业要正确定位,优化设计,实施与持续改进绩效考评,建立资源计划系统以应对不断变化的形势。     

Bias correction for parameter estimates of spatial point process models

When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best.     

全过程跟踪审计在高校新校区建设工程项目中的实施

开展高校新校区建设工程项目全过程跟踪审计,是以一整套法律法规为准绳和依据,遵照审计规范和原则,按照审计工作计划,采用合适的审计方式,分步有序地对工程建设项目的全过程进行监督评价,以期有效地控制工程造价,提高资金使用效益,促进学校建设工程目标的实现。     

Infill asymptotics for adaptive kernel estimators of spatial intensity

We apply the Abramson principle to define adaptive kernel estimators for the intensity function of a spatial point process. We derive asymptotic expansions for the bias and variance under the regime that n independent copies of a simple point process in Euclidean space are superposed. The method is illustrated by means of a simple example and applied to tornado data.