基于正交表的异方差估计方法改进

关于异方差模型的处理,方差估计及其性质研究是一个有意义的问题。本文针对一种基于正交表估计方差的非参数方法进行了改进。考虑到已有利用正交表的估计方法中,没有充分运用原始数据信息来确定因变量与自变量关系的不足,以及正交表使用中关于容差确定的不合理性,本文在这两方面进行了深入研究。模拟实验与实例分析表明,本文所提出的改进方法与原有正交表方法及HC4方法相比较,是一种更加有效的估计。     

The fractional-order SIS epidemic model with variable population size

In this work, we deal with the fractional-order SIS epidemic model with constant recruitment rate, mass action incidence and variable population size. The stability of equilibrium points is studied. Numerical solutions of this model are given. Numerical simulations have been used to verify the theoretical analysis.     

Normalizing and variance stabilizing transformations of multivariate statistics under an elliptical population

Summary Normalizing and variance stabilizing transformations of a sample correlation, multiple correlation and canonical correlation coefficients are obtained under an elliptical population. It is shown that the Fisher'sz-transformation is efficient for these statistics. A normalizing transformation is also studied for a latent root of a sample covariance matrix in an elliptical sample.     

改进种群多样性的双变异差分进化算法

差分进化算法(DE)是一种基于种群的启发式随机搜索技术,对于解决连续性优化问题具有较强的鲁棒性.然而传统差分进化算法存在种群多样性和收敛速度之间的矛盾,一种改进种群多样性的双变异差分进化算法(DADE),通过引入BFS-best机制(基于排序的可行解选取递减策略)改进变异算子"DE/current-to-best",将其与DE/rand/1构成双变异策略来改善DE算法中种群多样性减少的问题.同时,每个个体的控制参数基于排序自适应更新.最后,利用多个CEC2013标准测试函数对改进算法进行测试,实验结果表明,改进后的算法能有效改善种群多样性,较好地提高了算法的全局收敛能力和收敛速度.     

An extended discrete Ricker population model with Allee effects

Based on the classical discrete Ricker population model, we incorporate Allee effects by assuming rectangular hyperbola, or Holling-II type functional form, for the birth or growth function and formulate an extended Ricker model. We explore the dynamics features of the extended Ricker model. We obtain domains of attraction for the trivial fixed point. We determine conditions for the existence and stability of positive fixed points and find regions where there exist no positive fixed points, two positive fixed points one of which is stable and two positive fixed points both of which are unstable. We demonstrate that the model exhibits period-doubling bifurcations and investigate the existence and stability of the cycles. We also confirm that Allee effects have stabilization effects, by different measures, through numerical simulations.     

An age‐dependent population equation with delayed birth process

Within a semigroup framework, we discuss well posedness and qualitative behaviour of an age‐dependent population equation with delay in the birth process. Using positivity and Perron–Frobenius theory we obtain an explicit stability criterion. Copyright © 2004 John Wiley & Sons, Ltd.     

An algebraic study of BLUPs under two linear random-effects models with correlated covariance matrices

Assume that a pair of general Linear Random-effects Models (LRMs) are given with a correlated covariance matrix for their error terms. This paper presents an algebraic approach to the statistical analysis and inference of the two correlated LRMs using some state-of-the-art formulas in linear algebra and matrix theory. It is shown first that the best linear unbiased predictors (BLUPs) of all unknown parameters under LRMs can be determined by certain linear matrix equations, and thus the BLUPs under the two LRMs can be obtained in exact algebraic expressions. We also discuss algebraical and statistical properties of the BLUPs, as well as some additive decompositions of the BLUPs. In particular, we present necessary and sufficient conditions for the separated and simultaneous BLUPs to be equivalent. The whole work provides direct access to a very simple algebraic treatment of predictors/estimators under two LRMs with correlated covariance matrices.     

An improved general extra-gradient method with refined step size for nonlinear monotone variational inequalities

Extra-gradient method and its modified versions are direct methods for variational inequalities VI(Ω, F) that only need to use the value of function F in the iterative processes. This property makes the type of extra-gradient methods very practical for some variational inequalities arising from the real-world, in which the function F usually does not have any explicit expression and only its value can be observed and/or evaluated for given variable. Generally, such observation and/or evaluation may be obtained via some costly experiments. Based on this view of point, reducing the times of observing the value of function F in those methods is meaningful in practice. In this paper, a new strategy for computing step size is proposed in general extra-gradient method. With the new step size strategy, the general extra-gradient method needs to cost a relatively minor amount of computation to obtain a new step size, and can achieve the purpose of saving the amount of computing the value of F in solving VI(Ω, F). Further, the convergence analysis of the new algorithm and the properties related to the step size strategy are also discussed in this paper. Numerical experiments are given and show that the amount of computing the value of function F in solving VI(Ω, F) can be saved about 12–25% by the new general extra-gradient method.     

An identity for the Wishart distribution with applications

Let S_p×p have a Wishart distribution with unknown matrix Σ and k degrees of freedom. For a matrix T(S) and a scalar h(S), an identity is obtained for E_∑tr[h(S)T∑⁻¹]. Two applications are given. The first provides product moments and related formulae for the Wishart distribution. Higher moments involving S can be generated recursively. The second application concerns good estimators of ∑ and ∑⁻¹. In particular, identities for several risk functions are obtained, and estimators of ∑ (∑⁻¹) are described which dominate aS(bS⁻¹), a ≤ 1/k (b ≤ k − p − 1). [3] Ann. Statist. 7 No. 5; (1980) Ann. Statist. 8 used special cases of the identity to find unbiased risk estimators. These are unobtainable in closed form for certain natural loss functions. In this paper, we treat these case as well. The dominance results provide a unified theory for the estimation of ∑ and ∑⁻¹.     

An improved robust delay-dependent stability criterion for genetic regulatory networks with interval time delays

This paper proposes an improved robust delay-dependent criterion for stability of genetic regulatory networks with delays which vary in an interval. A modified Lyapunov-Krasovskii functional is used to derive a sufficient condition in terms of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms. The derived stability criterion is less conservative than ones in the literature. A numerical example and simulation results show the effectiveness of the proposed method.     

Asymptotic distributions of the latent roots of the covariance matrix with multiple population roots

An asymptotic expansion for large sample size n is derived by a partial differential equation method, up to and including the term of order n^?2, for the ₀F₀ function with two argument matrices which arise in the joint density function of the latent roots of the covariance matrix, when some of the population latent roots are multiple. Then we derive asymptotic expansions for the joint and marginal distributions of the sample roots in the case of one multiple root.     

An application of the Kriging method in global sensitivity analysis with parameter uncertainty

For structural systems with both epistemic and aleatory uncertainties, the effect of epistemic uncertainty on failure probability is measured by the variance based sensitivity analysis, which generally needs a “triple-loop” crude sampling procedure to solve and is time consuming. Thus, the Kriging method is employed to avoid the complex sampling procedure and improve the computational efficiency. By utilizing the Kriging predictor model, the conditional expectation of failure probability on the given epistemic uncertainty can be calculated efficiently. Compared with the Sobol’s method, the proposed one can ensure reasonable accuracy of results but with lower computational cost. Three examples are employed to demonstrate the reasonability and efficiency of the proposed method.     

An evaluation of the multivariate dispersion charts with estimated parameters under non‐normality

Various charts such as |S|, W, and G are used for monitoring process dispersion. Most of these charts are based on the normality assumption, while exact distribution of the control statistic is unknown, and thus limiting distribution of control statistic is employed which is applicable for large sample sizes. In practice, the normality assumption of distribution might be violated, while it is not always possible to collect large sample size. Furthermore, to use control charts in practice, the in‐control state usually has to be estimated. Such estimation has a negative effect on the performance of control chart. Non‐parametric bootstrap control charts can be considered as an alternative when the distribution is unknown or a collection of large sample size is not possible or the process parameters are estimated from a Phase I data set. In this paper, non‐parametric bootstrap multivariate control charts |S|, W, and G are introduced, and their performances are compared against Shewhart‐type control charts. The proposed method is based on bootstrapping the data used for estimating the in‐control state. Simulation results show satisfactory performance for the bootstrap control charts. Ultimately, the proposed control charts are applied to a real case study.     

Analysis of particle methods for structured population models with nonlocal boundary term in the framework of bounded Lipschitz distance

Recently developed theoretical framework for analysis of structured population dynamics in the spaces of nonnegative Radon measures with a suitable metric provides a rigorous tool to study numerical schemes based on particle methods. The approach is based on the idea of tracing growth and transport of measures which approximate the solution of original partial differential equation. In this article, we present analytical and numerical study of two versions of Escalator Boxcar Train algorithm which has been widely applied in theoretical biology, and compare it to the recently developed split‐up algorithm. The novelty of this article is in showing well‐posedness and convergence rates of the schemes using the concept of semiflows on metric spaces. Theoretical results are validated by numerical simulations of test cases, in which distances between simulated and exact solutions are computed using flat metric. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 30: 1797–1820, 2014