Linearized Models with Constraints of Type I

In nonlinear regression models with constraints a linearization of the model leads to a bias in estimators of parameters of the mean value of the observation vector. Some criteria how to recognize whether a linearization is possible is developed. In the case that they are not satisfied, it is necessary to decide whether some quadratic corrections can make the estimator better. The aim of the paper is to contribute to the solution of the problem.     

Linear Versus Quadratic Estimators in Linearized Models

In nonlinear regression models an approximate value of an unknown parameter is frequently at our disposal. Then the linearization of the model is used and a linear estimate of the parameter can be calculated. Some criteria how to recognize whether a linearization is possible are developed. In the case that they are not satisfied, it is necessary to take into account either some quadratic corrections or to use the nonlinear least squares method. The aim of the paper is to find some criteria for an ordering linear and quadratic estimators.     

可线性化非线性回归预测模型的剖析与改进

本文通过对可线性化非线性回归预测模型的剖析 ,得出了两个重要结论 .在此基础上 ,推导出了含有回归系数变化的可线性化非线性回归预测模型的一种有效改进方法——泰勒级数法 .最后 ,给出了一个应用实例     

不等式约束条件下部分线性回归模型的参数估计

本文研究了不等式约束条件下部分线性回归模型的参数估计问题，利用最优化方法和贝叶斯方法，给出了不等式约束条件下部分线性回归模型的最小二乘核估计和最佳贝叶斯估计，并且证明了在一定条件下，带约束条件的最小二乘核估计在均方误差意义下要优于无约束条件的最小二乘核估计。     

不等式约束条件下回归模型的参数估计及检验

本文研究了具有不等式约束条件的回归模型的参数估计，给出了检验的统计量和一个实例．     

右删失数据下非线性回归模型的经验似然推断

考虑随机右删失数据下非线性回归模型,提出了模型中未知参数的调整的经验对数似然比统计量.在一定的条件下,证明了.所提出的的统计量具有渐近χ~2分布,由此结果构造了兴趣参数的置信域.通过模拟研究,对经典的经验似然、调整的经验似然和非线性最小二乘方法在有限样本下进行了比较,并对氯离子浓度试验数据进行了分析.     

Type II Matrices and Their Bose-Mesner Algebras

Type II matrices were introduced in connection with spin models for link invariants. It is known that a pair of Bose-Mesner algebras (called a dual pair) of commutative association schemes are naturally associated with each type II matrix. In this paper, we show that type II matrices whose Bose-Mesner algebras are imprimitive are expressed as so-called generalized tensor products of some type II matrices of smaller sizes. As an application, we give a classification of type II matrices of size at most 10 except 9 by using the classification of commutative association schemes.     

多项Probit模型中回归系数的逆回归估计

本文将多项Probit模型推广到更一般的形式, 研究了推广的多项Probit模型的逆回归性质,给出了回归系数的逆回归估计方法, 并证明了在满足一些条件时估计是渐近正态的. 模拟表明逆回归估计方法有良好的表现.     

具有Holling-II型功能反应和交叉扩散的捕食-食饵模型正平衡解的存在性和不存在性

本文主要研究一类在齐次Dirichlet边界条件下带交叉扩散的Holling-II型捕食者-食饵模型正平衡解的存在性, 其中两个交叉扩散系数分别代表食饵远离捕食者的趋势和捕食者追逐食饵的趋势. 应用不动点指标理论得到了正平衡解存在的充分条件, 并进一步研究了正平衡解不存在的条件.     

基于pena距离的非线性回归模型的影响分析

基于pena距离统计量对非线性回归模型的影响分析进行了讨论,得到了非线性回归模型的pena距离公式,并对公式的分析性质以及其对高杠异常点的检测作用做出了相应的结论,得出了在一定条件下pena距离对异常点的检测优于Cook距离的结论,特别是对高杠杆异常点的检验,pena距离的效果更加明显,给出了实际数据检验结果,对方法的有效性进行了验证。     

Linearization conditions for regression models with unknown variance parameter

In the case of the nonlinear regression model, methods and procedures have been developed to obtain estimates of the parameters. These methods are much more complicated than the procedures used if the model considered is linear. Moreover, unlike the linear case, the properties of the resulting estimators are unknown and usually depend on the true values of the estimated parameters. It is sometimes possible to approximate the nonlinear model by a linear one and use the much more developed linear methods, but some procedure is needed to recognize such situations. One attempt to find such a procedure, taking into account the requirements of the user, is given in [4], [5], [3], where the existence of an a priori information on the parameters is assumed. Here some linearization criteria are proposed and the linearization domains, i.e. domains in the parameter space where these criteria are fulfilled, are defined. The aim of the present paper is to use a similar approach to find simple conditions for linearization of the model in the case of a locally quadratic model with unknown variance parameter ². Also a test of intrinsic nonlinearity of the model and an unbiased estimator of this parameter are derived.     

基于非线性回归模型的中国电力需求、资源、环境分析

中国电力需求的持续增长,给资源和环境带来了巨大的压力,而经济增长及其增长方式是电力需求发生变化的原因.中国从1995年以来GDP和全社会用电量时序统计结果具有明显的非线性变化特征,因而基于非线性回归模型的GDP、电力需求、资源和环境分析,可以为解决中国电力可持续发展问题提供一个理论依据.     

非线性回归模型中的约束拟似然

在非线性回归模型中,拟得分函数是一类线性无偏估计函数中的最优者(GodambeandHeyde(1987),朱仲义(1996)),而由拟得分函数得到的拟似然估计在由线性无偏估计函数得到的估计类中具有渐近最优性(林路(1999)).本文则研究非线性回归模型中的有偏估计函数理论,构造了参数的约束拟似然估计,得到了约束拟似然的局部最优性,局部改进了拟似然估计,从而扩充了线性模型中的有偏估计理论.     

Model Specification Tests in Nonparametric Stochastic Regression Models

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example.     

非线性回归校正模型在突变负荷预测中的研究及应用

非线性回归模型是中长期负荷预测的一种有效的方法,对常规变化趋势的负荷有很好的拟合性,但对有转折点的突变趋势或增长处于饱和阶段的负荷进行预测误差较大.通过对历史数据的最优分段,提出了非线性回归校正模型,可以很好地解决这个问题.实例表明,此模型在中长期负荷预测中是适用的,尤其对于有转折点的突变趋势,具有很高的预测精度.     

有滞留时间约束的两集束型装备调度模型

针对有滞留时间约束和并行加工的两集束型装备调度问题,分别推导了三类不等式约束条件,包括加工模块处于加工和空闲两种状态下的滞留时间约束、任意单个和两个搬运作业情况下的机械手搬运能力约束,以及缓冲模块能力约束,从理论上证明了并行加工模块等价加工时间的合理性,建立了以最小化生产周期为目标的混合整数规划模型.随机算例和基准算例的仿真结果验证了模型的可行性和有效性.     

删失数据下线性回归模型的参数估计

主要叙述在数据观测不完全的情况下,采用最小二乘法对线性回归模型回归系数的估计及估计量的渐进性质,并给出数据模拟．     

经典的用回归模型进行统计控制中的问题

利用回归模型进行统计控制,在实际工作中一直得到广泛应用。通常采用的方法是利用回归模型y^=a+bx进行逆估计,即根据回归模型的变换x=(y^-a)/b,由应变量Y的取值范围反推自变量X的取值范围。本文指出这种方法是很不合理的;进一步提出二种相对合理取代的统计方法。     

随机删失非参数回归模型的离差度量

主要研究了随机删失非参数固定设计回归模型的离差度量.首先利用随机删失非参数回归模型的性质和生存分布的Kaplan-Meier乘积限估计,将原模型转化为非参数回归模型进行研究;然后对模型作了离差度量分析,得到了模型的离差度量序列;最后通过实例分析,验证了上述诊断方法的有效性.     

Noise-induced Transitions for an SIV Epidemic Model with Medical-resource Constraints

We consider a stochastically forced epidemic model with medical-resource constraints. In the deterministic case, the model can exhibit two type bistability phenomena, i.e., bistability between an endemic equilibrium or an interior limit cycle and the disease-free equilibrium, which means that whether the disease can persist in the population is sensitive to the initial values of the model. In the stochastic case, the phenomena of noise-induced state transitions between two stochastic attractors occur. Namely, under the random disturbances, the stochastic trajectory near the endemic equilibrium or the interior limit cycle will approach to the disease-free equilibrium. Besides, based on the stochastic sensitivity function method, we analyze the dispersion of random states in stochastic attractors and construct the confidence domains (confidence ellipse or confidence band) to estimate the threshold value of the intensity for noise caused transition from the endemic to disease eradication.