Perfect simulation of an inventory model for perishable products

We study an inventory model for perishable products with a critical-number ordering policy under the assumption that demand for the product forms an i.i.d. sequence, so that the state of the system forms a Markov chain. Explicit calculation of the stationary distribution has proved impractical in cases where items have reasonably long lifetimes and for systems with large under-up-to levels. Using the recently developed coupling-from-the-past method, we introduce a technique to estimate the stationary distribution of the Markov chain via perfect simulation. The Markov chain that results from the use of a critical-number policy is particularly amenable to these simulation techniques, despite not being ordered in its initial state, since the recursive equations satisfied by the Markov chain enable us to identify specific demand patterns where the backward coupling occurs.     

The contagion effects of repeated activation in social networks

Demonstrations, protests, riots, and shifts in public opinion respond to the coordinating potential of communication networks. Digital technologies have turned interpersonal networks into massive, pervasive structures that constantly pulsate with information. Here, we propose a model that aims to analyze the contagion dynamics that emerge in networks when repeated activation is allowed, that is, when actors can engage recurrently in a collective effort. We analyze how the structure of communication networks impacts on the ability to coordinate actors, and we identify the conditions under which large-scale coordination is more likely to emerge.     

Positive Emotions,Instrumental Resources,and Organizational Network Evolution: Theorizing via Simulation Research

In the workplace, people seek positive emotional experiences as well as instrumental resources while doing their work. Yet we know little about how affective micro-dynamics drive the evolution of organizational networks, influence network trajectories, and determine macro outcomes such as collective affect and overall network structure. Given the lack of theory on affective micro-dynamics and network evolution, we propose a model that includes both affective and instrumental micro-mechanisms and use simulation methods to explore evolutionary dynamics and develop new theory. The core of our model is the empirically observed tendency for people to forego the acquisition of instrumental resources to avoid a decrease in positive emotion when choosing interaction partners. We conduct “experiments” with the simulation, considering the effects of the tradeoff, dispositional affect, resource inequality, and ingroup favoritism. The results show that dispositional affect and the tradeoff have considerable effects on network trajectories, collective affect, and resource transfer. We provide new theoretical propositions about affect in organizations.     

Critical values and powers for tests of uniformity of directions under multivariate normality

The Rayleigh, Ajne, Giné and two new tests of uniformity of directions are investigated as tests for multivariate normality when the population mean vector and covariance matrix are assumed to be unknown. The new tests include one which is designed especially to detect for bimodal alternatives and one which is designed to perform well under a wide variety of alternatives. Simulated percentile points are obtained under the assumption that the variates constitute a random sample from a multivariate normal distribution. Powers of the five tests are compared under alternatives in the bivariate as well as higher dimensional settings.     

炮位雷达智能应答器的设计与实现

介绍了一种炮位雷达智能应答器的系统构成、基本原理、主要功能及其实现.该智能应答器运用主控计算机计算出弹道仿真轨迹,再用可编程门阵列对接收的雷达信号进行数字信号处理,根据弹道轨迹产生调制的雷达目标回波信号.该智能应答器已完成了对炮位雷达信号的测试,取得了令人满意的效果.     

A Multivariate Extension of Inverse Gaussian Distribution Derived from Inverse Relationship

Abstract

We propose a new multivariate extension of the inverse Gaussian distribution derived from a certain multivariate inverse relationship. First we define a multivariate extension of the inverse relationship between two sets of multivariate distributions, then define a reduced inverse relationship between two multivariate distributions. We derive the multivariate continuous distribution that has the reduced multivariate inverse relationship with a multivariate normal distribution and call it a multivariate inverse Gaussian distribution. This distribution is also characterized as the distribution of the location of a multivariate Brownian motion at some stopping time. The marginal distribution in one direction is the inverse Gaussian distribution, and the conditional distribution in the space perpendicular to this direction is a multivariate normal distribution. Mean, variance, and higher order cumulants are derived from the multivariate inverse relationship with a multivariate normal distribution. Other properties such as reproductivity and infinite divisibility are also given.     

情景模拟教学法在建筑力学教学中的应用

情景模拟式教学是课程教学中经常采用的方法，也是切实培养学生将理论知识运用于实际的能力的有效方法。结合教学实践，探讨了在建筑力学课程教学中有效实施情景模拟教学的方法。     

产业竞争关系复杂网络上的竞争扩散研究

基于我国汽车零部件企业的数据,构建了有向加权的竞争关系复杂网络模型,在此网络上对竞争扩散效应进行仿真研究。研究发现,有向加权竞争网络中,外向点强度越大的节点发起的竞争行为导致的扩散效应越大;选择边权越大的相连节点发起竞争行为导致的扩散效应越大;由不同企业通过不同产品发起的竞争行为,其最终扩散的范围都是有限的,而且扩散的范围与发起企业所在的社团边界密切相关。此外,对仿真结果的经济学含义也进行了分析。     

A simulation study of balanced and antithetic bootstrap resampling methods

An extensive simulation study is conducted to compare the performance between balanced and antithetic resampling for the bootstrap in estimation of bias, variance, and percentiles when the statistic of interest is the median, the square root of the absolute value of the mean, or the median absolute deviations from the median. Simulation results reveal that balanced resampling provide better efficiencies in most cases; however, antithetic resampling is superior in estimating bias of the median. We also investigate the possibility of combining an existing efficient bootstrap computation of Efron (1990) with balanced or antithetic resampling for percentile estimation. Results indicate that the combination method does indeed offer gains in performance though the gains are much more dramatic for the bootstrap t statistic than for any of the three statistics of interest as described above.     

On finite mixture of two-component gompertz lifetime model

The Gompertz distribution has been used as a growth model, especially in epidemiological and biomedical studies. Based on Type I and II censored samples from a heterogeneous population that can be represented by a finite mixture of two-component Gompertz lifetime model, the maximum likelihood and Bayes estimates of the parameters, reliability and hazard rate functions are obtained. An approximation form due to Lindley (1980) is used in obtaining the corresponding Bayes estimates. The maximum likelihood and Bayes estimates are comparedvia a Monte Carlo simulation study.