A Comparison of the English Vocabulary Used by Children of Non-American Ancestry in Hawaii before they Reach the Age of Seven Years with that of Kindergarten Children in Continental United States

The authors investigated 2 issues concerning the power of latent growth modeling (LGM) in detecting linear growth: the effect of the number of repeated measurements on LGM's power in detecting linear growth and the comparison between LGM and some other approaches in terms of power for detecting linear growth. A Monte Carlo simulation design was used, with 3 crossed factors (growth magnitude, number of repeated measurements, and sample size) and 1,000 replications within each cell condition. The major findings were as follows: For 3 repeated measurements, a substantial proportion of samples failed to converge in structural equation modeling; the number of repeated measurements did not show any effect on the statistical power of LGM in detecting linear growth; and the LGM approach outperformed both the dependent t test and repeated-measures analysis of variance (ANOVA) in terms of statistical power for detecting growth under the conditions of small growth magnitude and small to moderate sample size conditions. The multivariate repeated-measures ANOVA approach consistently underperformed the other tests.     

模型设定偏误的蒙特卡洛模拟

设定偏误包括模型中遗漏变量和包含多余变量,会导致一些较严重的后果。在教学过程中,如果仅仅采用数学推导推演这些后果,由于公式复杂,学生接受较为困难;如果利用蒙特卡洛试验辅助教学,接受则会较为轻松。本研究利用GAUSS软件模拟模型设定偏误的后果。     

基于生物先验数据融合构建非平稳基因调控网络

为了构建基因调控网络,提出一个基于生物先验数据融合构建非平稳动态贝叶斯网络结构的方法.该方法基于高斯混合网络模型,改变点过程和独立的能量函数.利用可逆跳跃马尔科夫蒙特卡罗抽样算法,把整个非平稳过程分解成若干平稳子片断,推断网络结构以及先验数据对网络的影响.在仿真和生物数据上测试该方法,结果显示该方法提高了网络重构的精度.     

基于Logit模型和Monte Carlo方法的城市客运站选择行为研究

本文论述了研究的背景和意义,简单介绍基于随机效用理论的Logit模型和用于随机模拟的Monte Carlo方法,然后讨论运用Logit模型生成城市客运站选择概率,利用Monte Carlo方法模拟城市客运站选择行为,并以南京市城市客运站规划为实例,验证Logit模型和Monte Carlo方法的适用性,最后得出基于Logit模型和Monte Carlo方法是在一定程度上反映用户最优,可以与系统最优方法结合使用的结论。     

基于pair copula-GARCH模型的多资产组合VaR分析

提出了多资产组合风险分析的pair copula-GARCH 模型.相比于以往的copula-GARCH模型,它能够更好描述投资组合中两两资产间的尾部相关性的差异,从而更好地度量多资产组合间的相依结构.在此基础上,还探讨了pair copula-GARCH 模型下的多资产线性组合的VaR的计算方法.最后给出模型的实证分析.     

基于改进AGA的微电网优化管理研究

针对电动汽车无序充放电影响传统微电网稳定性及经济性问题,建立一种根据电动汽车随机负荷种类分时段调度模型,使用蒙特卡洛方法模拟电动汽车的充放电功率。同时,对传统微电网优化收敛速度慢、精度低等问题,提出一种改进自适应遗传优化算法（SAGA）。最优保存策略结合自适应调整交叉变异概率,解决遗传算法多样性问题,从而改善收敛速度与精度。通过建模及仿真计算,证明该方法在含电动汽车的风光柴储微电网优化中,能较快收敛到最优解,提高了微电网稳定性和经济性,具有良好的工程实用性。     

B-splines smoothed rejection sampling method and its applications in quasi-Monte Carlo integration

The rejection sampling method is one of the most popular methods used in Monte Carlo methods. It turns out that the standard rejection method is closely related to the problem of quasi-Monte Carlo integration of characteristic functions, whose accuracy may be lost due to the discontinuity of the characteristic functions. We proposed a B-splines smoothed rejection sampling method, which smoothed the characteristic function by B-splines smoothing technique without changing the integral quantity. Numerical experiments showed that the convergence rate of nearly O(N-1) is regained by using the B-splines smoothed rejection method in importance sampling.     

The Asymptotic Covariance Matrix and its Use in Simulation Studies

The asymptotic performance of structural equation modeling tests and standard errors are influenced by two factors: the model and the asymptotic covariance matrix Γ of the sample covariances. Although most simulation studies clearly specify model conditions, specification of Γ is usually limited to values of univariate skewness and kurtosis. We illustrate that marginal skewness and kurtosis are not sufficient to adequately specify a nonnormal simulation condition by showing that asymptotic standard errors and test statistics vary substantially among distributions with skewness and kurtosis that are identical. We argue therefore that Γ should be reported when presenting the design of simulation studies. We show how Γ can be exactly calculated under the widely used Vale–Maurelli transform. We suggest plotting the elements of Γ and reporting the eigenvalues associated with the test statistic. R code is provided.     

带电粒子漂移运动的Monte Carlo模拟

讨论了带电粒子在外电场以及无外电场作用下的漂移运动的物理模型,并且讨论了电流导致导体升温情况下带电粒子的运动,使用Monte Carlo方法对其进行了动画模拟,形象地表现出带电粒子在各种情况下的运动状态．     

Algorithm for solving the bi-level decision making problem with continuous variables in the upper level based on genetic algorithm

1 Introduction a The bi-level decision-making is a complex majorized problem. Its effective solution is not easy to obtain by traditional majorized methods. Reported methods to solve the bi-level decision making problem with continuous variables include neural network [1], Monte Carlo simulated annealing algorithm [2], etc. However, the efficiency and accuracy of such neural network methods are ideal and accompanied with a long iterative time and a slow convergence speed. In this paper, the …