Wegner Estimate for Random Magnetic Laplacian on {\mathbb{Z}^{2}}

We consider a two-dimensional magnetic Schr?dinger operator on a square lattice with a spatially stationary random magnetic field. We prove Anderson localization near the spectral edges. We use a new approach to establish a Wegner estimate that does not rely on the monotonicity of the energy on the random parameters.     

Estimate of Condition Number for Some Discrete Ill-Posed Equations

This paper extends the numerical method and the estimate of the condition number for some discrete ill-posed equations with positive definite matrix in [2] to the case with generalized positive definite matrix.     

Hierarchical Discrete Models of Competition for a Resource

A coupled pair of first order nonlinear discrete hierarchical age-structured models are applied to study two modes of intraspecific competitions; scramble and contest. The study focuses on several comparisons of the dynamical outcomes of the two competitions. For a constant resource, it is shown, using analytical and numerical approaches, that solutions of the contest model monotonically equilibrate, while solutions of the scramble model oscillate and become chaotic. It is also shown that the inherent net reproductive number of each population affects the comparison of equilibrium points in the two populations. By considering cases on the resource and model parameters, the local as well as the global stability of nontrivial equilibrium points are studied. The impact of a contest and a scramble consumer on a time dependent resource is considered numerically.     

Minimum Disparity Estimators for Discrete and Continuous Models

Disparities of discrete distributions are introduced as a natural and useful extension of the information-theoretic divergences. The minimum disparity point estimators are studied in regular discrete models with i.i.d. observations and their asymptotic efficiency of the first order, in the sense of Rao, is proved. These estimators are applied to continuous models with i.i.d. observations when the observation space is quantized by fixed points, or at random, by the sample quantiles of fixed orders. It is shown that the random quantization leads to estimators which are robust in the sense of Lindsay [9], and which can achieve the efficiency in the underlying continuous models provided these are regular enough.     

Sequential Discrete p-Facility Models for Competitive Location Planning

Two new models for duopolistic competitive discrete location planning with sequential acting and variable delivered prices are introduced. If locations and prices are assumed to be set once and for all by the players, the resulting bilevel program is nonlinear. Under the assumption that further price adjustments are possible, i.e., that a Nash equilibrium in prices is reached, the model can be simplified to a linear discrete bilevel formulation. It is shown that in either situation players should not share any locations or markets if they strive for profit-maximization.For the situation with price adjustments, a heuristic solution procedure is suggested. In addition, the bilevel models are shown to serve as a basis from which different well-known location models – as, for example, the p-median problem, the preemptive location problem and the maximum covering problem – can be derived as special cases.     

Mathematical Models of Discrete Self-Similarity

Natural phenomena which exhibit discrete self-similarity are under consideration. Earlier, self-similarity of some non-smooth phenomena was studied using the concept of log-periodicity, however there was a gap in this field. Recently it was attempted to fill this gap by concentrating on the study of a new concept of parametric-homogeneity (PH) based on the use of discrete group of coordinate dilations. It is argued that parametric-homogeneity can be helpful in the modelling of self-similar non-smooth phenomena. Some models of natural phenomena which have PH-features are presented and some properties of PH-functions are discussed. As an example of practical usage of these functions, the phenomenon of seismic activation prior to a major earthquake is considered.     

Limit Theorems for Risk Estimate in Models with Non-Gaussian Noise

The problem of constructing an estimate of a signal function from noisy observations, assuming that this function is uniformly Lipschitz regular, is considered. The thresholding of empirical wavelet coefficients is used to reduce the noise. As a rule, it is assumed that the noise distribution is Gaussian and the optimal parameters of thresholding are known for various classes of signal functions. In this paper a model of additive noise whose distribution belongs to a fairly wide class, is considered. The mean-square risk estimate of thresholding is analyzed. It is shown that under certain conditions, this estimate is strongly consistent and asymptotically normal.     

简化的Becker模型参数估计的D－最优设计

本文利用椭圆型偏微分方程极值原理和对称多项式，解决了三分量简化的＆Ｂｅｃｋｅｒ模型（Ⅱ）和（Ⅲ）的参数估计的Ｄ－最优设计．     

Stability Analysis for Discrete Biological Models Using Algebraic Methods

This paper is concerned with stability analysis of biological networks modeled as discrete and finite dynamical systems. We show how to use algebraic methods based on quantifier elimination, real solution classification and discriminant varieties to detect steady states and to analyze their stability and bifurcations for discrete dynamical systems. For finite dynamical systems, methods based on Gr?bner bases and triangular sets are applied to detect steady states. The feasibility of our approach is demonstrated by the analysis of stability and bifurcations of several discrete biological models using implementations of algebraic methods.     

Markov Property in Discrete Schur-constant Models

This paper is concerned with Schur-constant survival models for discrete random variables. Our main purpose is to prove that the associated partial sum process is a non-homogeneous Markov chain. This is shown in three different situations where the random variables considered take values in the sets ₀, {0,1} or {0,…,m}, m ≥ 2. The property of Schur-constancy is also compared for these three cases.     

Discrete ABP Estimate and Convergence Rates for Linear Elliptic Equations in Non-divergence Form

We design a two-scale finite element method (FEM) for linear elliptic PDEs in non-divergence form \(A(x) : D^2 u(x) = f(x)\) in a bounded but not necessarily convex domain \(\Omega \) and study it in the max norm. The fine scale is given by the meshsize h, whereas the coarse scale \(\epsilon \) is dictated by an integro-differential approximation of the PDE. We show that the FEM satisfies the discrete maximum principle for any uniformly positive definite matrix A provided that the mesh is face weakly acute. We establish a discrete Alexandroff–Bakelman–Pucci (ABP) estimate which is suitable for finite element analysis. Its proof relies on a discrete Alexandroff estimate which expresses the min of a convex piecewise linear function in terms of the measure of its sub-differential, and thus of jumps of its gradient. The discrete ABP estimate leads, under suitable regularity assumptions on A and u, to pointwise error estimates of the form

$$\begin{aligned} \Vert \,u - u^{\epsilon }_h\,\Vert _{L^{\infty }(\Omega )} \le \, C(A,u) \, h^{2\alpha /(2 + \alpha )} \big | \ln h \big | \qquad 0< \alpha \le 2, \end{aligned}$$

provided \(\epsilon \approx h^{2/(2+\alpha )}\). Such a convergence rate is at best of order \( h \big | \ln h \big |\), which turns out to be quasi-optimal.

     

一类线性混合模型的谱分解估计

谱分解估计(SDE)是新近提出的关于线性混合模型参数的一种新的估计方法,此方法的一个突出特点是同时给出固定效应参数和方差分量的显式解估计．本文就含两个方差分量的线性混合模型,对谱分解估计的性质做了进一步的研究,获得了方差分量的SDE和方差分析估计相等的充分必要条件,证明了在一定的条件下方差分量的SDE为一致最小方差无偏估计．     

广义线性模型中方差函数的非参数估计

本文提出了$\sigma(u)$的一种改进的估计$\wh\sigma_n(u)$, 在一定的条件下证明了$\sup\limits_{u}|\wh\sigma_n(u)-\sigma(u)|$相对于[1]中的估计以更快的速度依概率收敛于0, 并修正了定义区间.     

广义线性模型中方差函数的非参数估计

本文提出了$\sigma(u)$的一种改进的估计$\wh\sigma_n(u)$, 在一定的条件下证明了$\sup\limits_{u}|\wh\sigma_n(u)-\sigma(u)|$相对于[1]中的估计以更快的速度依概率收敛于0, 并修正了定义区间.