Quasi-maximum likelihood estimators in generalized linear models with autoregressive processes

The paper studies a generalized linear model(GLM)y_t = h(x_t~T β) + ε_t,t = l,2,...,n,where ε_1 = η_1,ε_1 =ρε_t +η_t,t = 2,3,...;n,h is a continuous differentiable function,η_t's are independent and identically distributed random errors with zero mean and finite variance σ~2.Firstly,the quasi-maximum likelihood(QML) estimators of β,p and σ~2 are given.Secondly,under mild conditions,the asymptotic properties(including the existence,weak consistency and asymptotic distribution) of the QML estimators are investigated.Lastly,the validity of method is illuminated by a simulation example.     

Sufficient conditions for error bounds and linear regularity in Banach spaces

In this paper, we study error bounds for lower semicontinuous functions defined on Banach space and linear regularity for finitely many closed subset in Banach spaces. By using Clarke＇s subd- ifferentials and Ekeland variational principle, we establish several sufficient conditions ensuring error bounds and linear regularity in Banach spaces.     

Subordination Results for p-Valent Meromorphic Functions Associated with a Linear Operator

In this paper, by making use of the Hadamard products, we obtain some subordination results for certain family of meromorphic functions defined by using a new linear operator.     

基于单纯形分布的比例数据的回归分析

很多应用领域中的实验结果都表达成连续比例型数据,这类数据通常度量成为百分比、比率或比例,并取值于单位区间.为了采用弥散模型中的单纯形分布来模拟此类实验结果,本文首先研究单纯形分布的部分重要性质,在回归分析中参数估计和统计推断需要运用这些性质.模拟研究表明,当所研究情形不满足分布假设时,单纯形回归模型比Beta回归和分对数-正态回归模型更为稳健.通过对体外造血干细胞移植技术的真实数据分析,本文阐释这种方法和它针对异常值的稳健性.在R软件中,单纯形回归可以由程序包"simplexreg"实现,读者可以自行下载这个程序包,地址为http://my.zju.edu.cn/share/2466293(验证码:7919).     

Robust linear optimization under matrix completion

Linear programming models have been widely used in input-output analysis for analyzing the interdependence of industries in economics and in environmental science.In these applications,some of the entries of the coefficient matrix cannot be measured physically or there exists sampling errors.However,the coefficient matrix can often be low-rank.We characterize the robust counterpart of these types of linear programming problems with uncertainty set described by the nuclear norm.Simulations for the input-output analysis show that the new paradigm can be helpful.     

Exact analytical inversion of TSK fuzzy systems with singleton and linear consequents

In literature, exact inversion methods for TSK fuzzy systems exist only for the systems with singleton consequents. These methods have binding limitations such as strong triangular partitioning, monotonic rule bases and/or invertibility check. These extra limitations lessen the modeling capabilities of the TSK fuzzy systems. In this study, an exact analytical inversion method for TSK fuzzy systems with singleton and linear consequents is presented. The only limitation of the proposed method is that the inversion variable should be represented by piecewise linear membership functions (PWL-MFs). In this case, the universe of discourse of the inversion variable is divided into specific regions in which only one linear piece exists for each PWL-MF at most. In the proposed method, the analytical formulation of TSK fuzzy system is expressed in terms of the inversion variable by using linear equations of PWL-MFs. Thus, the fuzzy system output in any region can be obtained by using the appropriate parameters of the linear equations of PWL-MFs defined within the related region. This expression provides a way to obtain linear and quadratic equations in terms of the inversion variable for TSK fuzzy systems with singleton and linear consequents, respectively. So, it becomes very easy to find exact inverse solutions for each region by using explicit analytical solutions for linear or quadratic equations. The proposed inversion method has been illustrated through simulation examples.     

Probabilistic solution of random homogeneous linear second-order difference equations

This paper deals with the computation of the first probability density function of the solution of random homogeneous linear second-order difference equations by the Random Variable Transformation method. This approach allows us to generalize the classical solution obtained in the deterministic scenario. Several illustrative examples are provided.     

基于提前期压缩的两阶段供应链的契约协调

研究了基于提前期压缩的信息对称和信息不对称两种情况下的供应链协调问题,重点解决了在信息不对称时采用线性转移支付策略解决供应链的不协调问题.当压缩提前期时,制造商的成本增加,成本的增加值信息对销售商有对称和不对称两种情况.在信息对称时采用收益共享契约可以实现供应链的协调;在信息不对称,采用收益共享契约时,为了激励制造商,销售商不得不对制造商生产成本的不确定性付出成本,导致利润下降,而制造商由于拥有私有信息而使得利润增加,所以整个供应链并没有达到集中决策时的水平,只得到了帕累托改善的次优结果.创新点在于采用线性转移支付策略实现了供应链的协调,达到了帕累托最优,解决了收益共享契约不能实现供应链协调的问题.最后通过算例进行了说明.     

基于多元线性回归模型的东北地区需水量分析

多元线性回归模型在社会、经济、技术以及众多自然科学研究领域中已被广泛使用,某个地区需水量应与该地区多种因素有关,故选取东北地区的GDP、水库蓄水总量、人均可支配收入、城市绿地面积和工业用水量等5个因素,借助MATLAB软件阐明了多元线性回归模型在东北地区需水量分析中的应用.并通过皮尔森相关性检验、拟合优度检验、F检验、t检验和残差分析的方法对模型进行优化,得到了准确可靠的多元线性回归模型,此模型具有拟合程度高、简易、直观等优势,为多元线性回归模型在需水量分析中的应用提供了有力参考.