非单调二元非线性算子方程组的迭代求解

利用锥与半序理论和混合单调算子理论 ,讨论 Banach空间中非单调二元非线性算子方程组解的存在性与唯一性 ,并给出收敛于方程组解的迭代序列和误差估计 ,改进和推广了混合单调算子方程和一元算子方程的某些相应结果 .     

Shrinkage Structure of Partial Least Squares

Partial least squares regression (PLS) is one method to estimate parameters in a linear model when predictor variables are nearly collinear. One way to characterize PLS is in terms of the scaling (shrinkage or expansion) along each eigenvector of the predictor correlation matrix. This characterization is useful in providing a link between PLS and other shrinkage estimators, such as principal components regression (PCR) and ridge regression (RR), thus facilitating a direct comparison of PLS with these methods. This paper gives a detailed analysis of the shrinkage structure of PLS, and several new results are presented regarding the nature and extent of shrinkage.     

A further note on a theorem on the difference of the generalized inverses of two nonnegative definite matrices

Andrews and Phillips (1986) gave a simplified proof for the result that established the nonnegative definiteness of the difference of the Moore-Penrose inverses of two nonoegative definite matrices, a result originally due to Milliken and Akdeniz (1977), The purpose of this paper is to offer a simple proof for a generalization of this result,     

3-状态部分2-树网络可靠度的一个多项式时间算法

本文利用3-状态设备网络可靠度计算归约公式,结合Wald.J.A.-Colbourn C.J.[1]算法(简称为W-C算法2),给出了3-状态部分2-树网络可靠度的一个多项式时间算法.     

方向导数和偏导数

通过对方向导数和偏导数两者间区别与联系的论述，揭示了它们是同属于函数变化率问题的两个平行的不同的概念．     

Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework

We develop a new quantile‐based panel data framework to study the nature of income persistence and the transmission of income shocks to consumption. Log‐earnings are the sum of a general Markovian persistent component and a transitory innovation. The persistence of past shocks to earnings is allowed to vary according to the size and sign of the current shock. Consumption is modeled as an age‐dependent nonlinear function of assets, unobservable tastes, and the two earnings components. We establish the nonparametric identification of the nonlinear earnings process and of the consumption policy rule. Exploiting the enhanced consumption and asset data in recent waves of the Panel Study of Income Dynamics, we find that the earnings process features nonlinear persistence and conditional skewness. We confirm these results using population register data from Norway. We then show that the impact of earnings shocks varies substantially across earnings histories, and that this nonlinearity drives heterogeneous consumption responses. The framework provides new empirical measures of partial insurance in which the transmission of income shocks to consumption varies systematically with assets, the level of the shock, and the history of past shocks.     

基于智能体的大批量定制体系结构及协同方法

为满足大批量定制运营过程中动态特性和协同管理的要求,本文构建了一个多智能体的大批量定制体系结构,描述了大批量定制下各个智能体的规范,提出了3层协同模型,使用局部全局计划来解决大批量定制协同问题,并介绍了该方法在大批量定制协同的实例应用.     

Risk of Error and the Kappa Coefficient of a Binary Diagnostic Test in the Presence of Partial Verification

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or through positive and negative predictive values. Another way to describe the validity of a binary diagnostic test is the risk of error and the kappa coefficient of the risk of error. The risk of error is the average loss that is caused when incorrectly classifying a non-diseased or a diseased patient, and the kappa coefficient of the risk of error is a measure of the agreement between the diagnostic test and the gold standard. In the presence of partial verification of the disease, the disease status of some patients is unknown, and therefore the evaluation of a diagnostic test cannot be carried out through the traditional method. In this paper, we have deduced the maximum likelihood estimators and variances of the risk of error and of the kappa coefficient of the risk of error in the presence of partial verification of the disease. Simulation experiments have been carried out to study the effect of the verification probabilities on the coverage of the confidence interval of the kappa coefficient.     

Structural Nested Models and Standard Software: A Mathematical Foundation through Partial Likelihood

Abstract.  In observational studies treatment may be adapted to the patient's state during the course of time. These covariates may in turn also react on the treatment under study, and so on. This makes it hard to distinguish between treatment effect and selection bias. Structural nested models aim at estimating treatment effect in such complicated situations, even when treatment may change at any time. We show that structural nested models can often be calculated with standard software, by using standard models to predict treatment as a tool to estimate treatment effect. Robins ( Survival analysis, Volume 6 of Encyclopedia of Biostatistics , John Wiley and Sons, Chichester, 1998) conjectured this, but so far it was unproven. We use a partial likelihood approach to choose the estimators and tests as a subclass of the estimators and tests in Lok (math. ST/0410271 at http://arXiv.org , 2004). We show that this is the class of estimators and tests that can be calculated with standard software. The estimators are consistent and asymptotically normal, and have interesting asymptotic properties.     

含时滞的偏泛函微分方程解的稳定性

采用不等式估值方法 ,对含时滞的偏泛函微分方程解的稳定性进行了讨论 ,获得了零解渐近稳定的简洁判据