AANA误差下半参数回归模型中估计量的相合性

考虑如下半参数回归模型y_i=x_iβ+g(t_i)+σ_ie_i,i=1,2,…,n,n≥1,其中σ_i~2=f(u_i),(x_i,t_i,u_i)为已知设计点列.在适当的条件下,当误差为AANA变量时,本文研究了未知参数β和未知函数g的最小二乘估计与加权最小二乘估计的相合性,特别是p(p1)阶矩相合性和完全相合性,所得结果推广了误差为NA变量的相应结论.     

带多余位置一刻度参数的非参数两样本问题

<正> 设x_1,…,x_m,y_1,…,y_n为m+n个独立随机变量,x_i有连续分布函数F,y_i有连续分布函数G.要依据这些观测值x_i,i=1,…,m,y_i,j=1,…,n来检验假设(注意F和G都是未知的) H_o:存在常数A和B,B>0,致     

鞅差误差下线性EV模型最小二乘估计的中偏差

研究了线性EV模型:η_i=θ+βx_i+ε_i,ξ_i=x_i+δ_i,1≤i≤n.当误差(ε_i,δ_i)为鞅差序列情形时,讨论了未知参数β和θ的最小二乘估计的中偏差问题.     

非参数回归函数的基于截尾数据的估计

本文考虑截尾数据情况下非参数回归函数m(x)=E(Y|x)的估计。具体地讲,我们面对的是这样的数学模型:T是与(X,Y)独立的随机变量,我们观测到的不是Y本身,而是Z=min(Y,T)及δ=[Y≤T]。今有训练样本{(X_i,Z_i,δ_i)}_(i-1)及当前样本(X,z,δ),记ξ_i(·)=[z_i≥·], N~ (·)=sum from i=1 to n ξ_i(·), V_n(·)=multiply from i=1 to n{1 N~ (z_i)/2 N~ (z_i)}~[δ_i=_i<0], U_n(·)=sum from i=1 to n Wnt(x)ξ_i(·), 令 m_n(x)=integral from 0 to u_n U_n(y)|V_n(y)dy, 其中u_n=F_2~(-1)(n~(-a)),0<α<1/2为一实常数,F_2(·)=P(Y≥·)为Y的(右侧)分布函数。在权函数{W_(ni)(x)}_(i=1)~n及(X,Y,T)的分布函数满足一组条件下,我们证明了m_n(x)为m(x)的强相合估计,即:m_n(x)→m(x),a.s.(n→ ∞).     

多参数同时估计的容许性

令 X_1,…,X_n 是一串独立随机变量,且 X_1～P_(θ_i)θ_i∈(?)_i,(i=1,2,…,n),假设估计θ_i 的损失函数为 L(θ_i,d_i),δ_i(X_i)是仅依赖 X_i,θ_i 的一个容许估计(i=1,2,…,n).现在我们要同时估计(θ_1,…,θ_n)′(?)θ,其损失函数取为 sum from i=1 to n L(θ_i,d_i),那么(δ_i(X_1),…,δ_n(X_n))′是θ的容许估计吗?早在50年代,Stein 就证明了,在 n≥3,X_i～N(θ_i,1),L(θ_i,d_i)=(θ_i-d_i)~2条件下,上述结论不成立.近20余年,很多作者也研究了这个问题,指出 Stein 的现象对许多分布,例如 Poisson 分布,Gama 分布,负二项分布及位置参数估计皆存在.但在什么条件下,(δ,(X_1),…,δ_n(X))′是容许的则很少研究,仅仅有少数特殊情况下的结果(见[3]).本文给出了相当一般的充分条件(定理1.1),利用定理1.1,研究了 L(θ_i,d_i)=λ(θ_i)(g(θ_i)-d_i)~2时,结论成立的充分条件(定理2.1).还给出了多个位置参数,Pitman 估计为容许的充分条件.最后一节给出了五个具体例子,它包括在平方损失下,多个正态密度及分布函数的容许估计;参数自然区间 为有限区间之指数族分布,在平方损失下,同时估计多个均值的线性容许估计;若 X_i～Poisson 分布 P_(2_i),i=1,2,…,n(a_1x_1,…,a_nx_n)′在损失函数sum from i=1 to n     

CONSISTENT NONPARAMETRIC ESTIMATION OF ERROR DISTRIBUTIONS IN LINEAR MODEL'

For the linear model y_i=x_iθ e_i, i=1, 2,…, let the error sequence {e_i}_i=1 be iidr.v.'s, with unknown density f(x). In this paper,a nonparametric estimation method based onthe residuals is proposed for estimating f(x) and the consistency of the estimators is obtained.     

线性模型中φ-混合误差下误差方差估计的强收敛速度

考虑线性回归模型一、引言和引理y_i=x_i′β e_i,i=1,2,…,(1)这里{x_i}为已知的 d-维向量序列,β为未知的回归系数向量,{e_i}为随机误差序列,满足Ee_i=0,0相似文献   

三次样条的Hermite-Birkboff插值

设Δ:0=x_0相似文献   

线性模型中\varphi-混合误差下误差方差估计的强收敛速度

考虑线性回归模型一、引言和引理y_i=x_i′β+e_i,i=1,2,…,(1)这里{x_i}为已知的 d-维向量序列,β为未知的回归系数向量,{e_i}为随机误差序列,满足Ee_i=0,0相似文献   

平方损失下的最近邻预测理论

§1.引言 设在R~d×R~1(d≥1)取值的变量(x,θ),(x_i,θ_i),i=1,…,n相互独立,此处(X_i,θ_i)是已知样本,X之值已观测,而要依据它们去预测θ之值。引进平方损失(θ—a)~2,即用a去预测θ时,所蒙受的损失。 若知道了(x,θ)的联合分布,则风险最小的预测,即Bayes预测 δ(x)=E(θ|X=x),可无需求助于样本(X_i,θ_i),i=1,…,n而定出。当X=x时,此预测之后验风险     

Method of weighted residuals as applied to nonlinear differential equations

A new method for solving a class of nonlinear boundary-value problems is presented. In this method, the nonlinear equation is linearized by guessing an initial solution and using it to evaluate the nonlinear terms. Next, a method of weighted residuals is applied to transform the linearized form of the boundary value problem to an initial value problem. The second (improved) solution is obtained by integrating the initial value problem by a fourth order Runge-Kutta scheme. The entire process is repeated until a desired convergence criterion is achieved.     

Nonlinear dynamical systems of trajectory design for 3D horizontal well and their optimal controls

The trajectory design of horizontal well is a optimal control problem of nonlinear multistage dynamical system. It is often sought using trial-and-error methods, but these methods depend on experience of designers and workers. In this paper, we create new optimal control model of nonlinear dynamical system for the trajectory design of horizontal well. Several properties are discussed. Uniform design method is used to choose the initial points in the feasible region. We demonstrate how to decompose the feasible region into finite subregions in which improved Hook–Jeeves algorithm is employed to search optimal solution. Finally, the feasible optimization algorithm is constructed to find the optimal solution of the system. Several results show the validity of our algorithm. This is preferable, since our method is independent of the experience.     

基于熵权TOPSIS-PSO-ELM的制造企业绿色创新能力评价模型及实证研究

为客观和准确地评价制造企业绿色创新能力,本文构建了制造企业绿色创新能力评价指标体系,提出了基于熵权TOPSIS的粒子群(PSO)优化极限学习机(ELM)集成学习算法的制造企业绿色创新能力评价模型。首先运用熵权法客观确定指标权重,结合TOPSIS测度并综合评价制造企业绿色创新能力,然后将评价值作为先验样本进行极限学习机的训练与测试,训练过程中利用PSO优化极限学习机的网络结构与连接权值,从而对绿色创新能力进行全面的分析和评价。最后以60家制造企业为例进行实证分析,并将熵权TOPSIS-PSO-ELM算法与极限学习机回归拟合算法对比,结果表明:基于熵权TOPSIS-PSO-ELM模型所得评价结果较已有方法更为准确可靠。此外,为进一步提高我国制造企业绿色创新发展能力提出了理论建议。     

基于分组数据的回归系数的估计

本文讨论了如何去解决基于分组数据下的回归系数的估计问题.本文所讨论的基于分组数据下的回归模型与经典回归模型的差异在于因变量的观测值为分组数据,即我们只知道它落于事先确定的一组区间中的某一区间,而不知道它的具体值;而经典回归模型的因变量观测值则是一个确定的数值.我们用MLE去估计回归系数,但是此时的MLE无显式解,所以寻找一个合适的迭代算法就成了问题的关键.我们选择利用Bayes计算方法中的EM算法来获得估计量的迭代公式.随机模拟显示了所得估计的有效性.     

Investigation and reduction of variance of a weighted estimate in numerical statistical simulation

The efficiency of the “value” and “partial value” modeling related to the construction of a modeling distribution for an auxiliary random variable by multiplying the initial density by a value function is investigated. The value function usually corresponds to a solution of the adjoint equation. Conditions under which the value modeling of the initial distribution reduces the variance compared to the direct simulation are obtained. It is proved that the variance of the weighted estimate is bounded in the case of the partial value modeling. This proposition provides a basis for a method for determining whether or not the variance of the weighted estimate is bounded. This method uses the majorizing adjoint equation. Using a practically important problem in transport theory as an example, the asymptotic optimization of the distribution of the mean free path is presented. The application of the proposed method of the investigation of the variance boundedness for the analysis of the classical exponential transformation method of simulating the mean free path of a particle in the one-dimensional and the spherical variants is discussed.     

Energy Methods for Problems with Nonhomogeneous Boundary Conditions

This paper employs the weighted energy method to derive estimates for the dynamic behavior of solutions to boundary and initial boundary value problems with nonhomogeneous boundary conditions. In particular, the method is applied to the heat and Laplace equations in a bounded or unbounded region. Extensions to related equations are also studied. Similar estimates but for the spatial behavior is obtained for the heat equation and the backward in time heat equation. Results for blow-up in finite time of solutions to certain nonlinear equations are generalized to include nonhomogeneous boundary conditions, while solutions that vanish on part of the boundary are briefly discussed in the final section.     

基于区间数据最大似然估计的新方法

In this paper, we study the two-parameter maximum likelihood estimation (MLE)problem for the GE distribution with consideration of interval data. In the presence of interval data, the analytical forms for the restricted MLE of the parameters of GE distribution do not exist. Since interval data is kind of incomplete data, the EM algorithm can be applied to compute the MLEs of the parameters. However the EM algorithm could be less effective.To improve effectiveness, an equivalent lifetime method is employed. The two methods are discussed via simulation studies.     

Optimized pump scheduling in water distribution systems

A method based on nonlinear programming for determining the optimal operation of general water distribution systems containing multiple sources and reservoirs is presented. The problem is formulated and solved so that, given the forecasted demands for the coming 24 hours, the initial and final conditions in the reservoirs, the unit and maximum demand electricity charge, and the constraints in the hydraulic properties of all system components, an optimized pumping schedule is found. An optimization algorithm which employs the generalized reduced gradient method and the nonlinear sensitivity analysis has been developed for a basic scheduling problem in which only unit charges are considered. The maximum demand charge, which is weighted by varying degrees from day to day, is incorporated into the scheduling problem. The algorithm uses a feasible initial solution as the starting solution and iterates so that all the interim solutions are feasible.The work described here was undertaken at Brunel University and the University of Durham, UK. The authors are grateful to SERC for dunding the project and also thank Professor Uri Shamir, Department of Civil Engineering, Israel Institute of Technology for his review and many useful comments.     

空间自相关地理加权回归模型的估计

地理加权回归作为一类能有效处理回归分析中空间非平稳性现象的建模技术,在多类问题的研究得到了广泛的应用.主要讨论这类空间计量经济学模型在空间自相关情形下的估计问题.首先,对于因变量含有空间滞后项的地理加权回归模型,分别给出了局部似然估计和两步估计两种方法.其次,考虑了误差空间自相关下地理加权回归模型的估计问题.     

An extension of the Tau numerical algorithm for the solution of linear and nonlinear Lane–Emden equations

The purpose of this paper is to present a numerical algorithm for solving the Lane–Emden equations as singular initial value problems. The proposed algorithm is based on an operational Tau method (OTM). The main idea behind the OTM is to convert the desired problem to some operational matrices. Firstly, we use a special integral operator and convert the Lane–Emden equations to integral equations. Then, we use OTM to linearize the integral equations to some operational matrices and convert the problem to an algebraic system. The concepts, properties, and advantages of OTM and its application for solving Lane–Emden equations are presented. Some orthogonal polynomials are also used to reduce the volume of computations. Finally, several experiments of Lane–Emden equations including linear and nonlinear terms are given to illustrate the validity and efficiency of the proposed algorithm. Copyright © 2012 John Wiley & Sons, Ltd.