不确定混合时滞系统的指数稳定性判据

考虑同时含有参数不确定和混合时滞的动力系统的指数稳定性问题,利用参数依赖的Lyapunov函数和分解时滞项系数矩阵的方法,以线性矩阵不等式的形式给出了保守性更低的稳定性的充分条件.数值算例验证了该方法的有效性.     

高能e+e-碰撞产生的喷注内部的动力学起伏的蒙特卡洛研究

用蒙特卡洛方法研究了91.2GeV e+e-碰撞产生的双喷注事件子样本和双喷注事件中的单喷注子样本内的动力学起伏.结果表明,喷注内部的动力学起伏的各向异性随着截断参数ycut的变化而明显地改变.存在一个转变点,在该点处动力学起伏在纵-横平面是各向异性的,而在横平面是各向同性的,由此得到了产生喷注的一个标度.     

连续控制系统的离散相似－可调参数法仿真

本文讨论的连续控制系统仿真方法是基于离散相似和可调数值积分法相结合的一种快速数字仿真方法．文中推导了基本仿真模型，并讨论了系统仿真的实现．实例表明，此方法是可行的．     

钢筋混凝土恢复力特征参数计算方法的对比

介绍了钢筋混凝土恢复力特征参数的理论计算方法和基于试验数据的经验公式 ,用这两种方法同时计算了 10个钢筋混凝土框架。两种方法结果的对比表明 :经验公式的精度是能够为工程实际所接受的     

光学分辨率判据和可见度

本文研究了两个非相干点光源靠近时，在圆孔的夫琅和费衍射下两个光斑之间可见度的变化情况。对于不同判据，可见度有明显差异，表现出各种判据的不一致性。同时还研究了光栅的夫琅和费衍射，当两明条纹很靠近时，可见度的变化情况。同样可以得到各判据相应的数值。     

Selecting the optimum k in ridge regression

Two ridge rules are proposed for selecting the optimal k in ridge regression . Since the sampling distribution of the proposed rules are mathematically in tractable , a Monte Carlo study is conducted to examine their statisticl properties . Numerical results of the simulations in dicate that the performance of ridge rules depends upon the risk function used. Nevertheless, one of the ridge rules does produce a smaller mean squared error than the least squares estimator with the probability greater than 0.57 for all situations.     

Estimations of a threshold parameter in cox regression

Therneau et al (1990) used martingale residual plots to study the threshold effect of some covariates in a proportional hazard regression model for survival data subject to right censoring. We show that the maximum partial likelihood estimate provides an asymptotically consistent estimator for the unknown threshold. This procedure is illustrated by applying it to a data set from a cohort of patients with B-lineage leukemia treated at St. Jude Children's Research Hospital.     

Computation of probability and non-centrality parameter of a non-central f-distribution

The small sample properties of the score function approximation to the maximum likelihood estimator for the three-parameter lognormal distribution using an alternative parameterization are considered. The new set of parameters is a continuous function of the usual parameters. However, unlike with the usual parameterization, the score function technique for this parameterization is extremely insensitive to starting values. Further, it is shown that whenever the sample third moment is less than zero, a local maximum to the likelihood function exists at a boundary point. For the usual parameterization, this point is unattainable. However, the alternative parameter space can be expanded to include these boundary points. This procedure results in good estimates of the expected value, variance, extreme percentiles and other parameters of the distribution even in samples where, with the typical parameterization, the estimation procedure fails to converge.     

Change Point Detection in The Skew-Normal Model Parameters

Bayesian inference under the skew-normal family of distributions is discussed using an arbitrary proper prior for the skewness parameter. In particular, we review some results when a skew-normal prior distribution is considered. Considering this particular prior, we provide a stochastic representation of the posterior of the skewness parameter. Moreover, we obtain analytical expressions for the posterior mean and variance of the skewness parameter. The ultimate goal is to consider these results to one change point identification in the parameters of the location-scale skew-normal model. Some Latin American emerging market datasets are used to illustrate the methodology developed in this work.     

Refining binomial confidence intervals

A method for refining an equivariant binomial confidence procedure is presented which, when applied to an existing procedure, produces a new set of equivariant intervals that are uniformly superior. The family of procedures generated from this method constitute a complete class within the class of all equivariant procedures. In certain cases it is shown that this class is also minimal complete. Also, an optimally property, monotone minimaxity, is investigated, and monotone minimax procedures are constructed.