非参数计量经济联立模型的局部线性广义矩估计

联立方程模型在经济政策制定、经济结构分析和经济预测方面起重要作用。本文在随机设计(模型中所有变量为随机变量)下,提出了非参数计量经济联立模型的局部线性广义矩估计并利用概率论中大数定理和中心极限定理在内点处研究了它的大样本性质,证明了它的一致性和渐近正态性。它在内点处的收敛速度达到了非参数函数估计的最优收敛速度。     

A Note on the Computation of the Mean Random Consistency Index of the Analytic Hierarchy Process (Ahp)

In this paper, we use Saaty's Eigenvector Method and the Power Method as well as =1, 2, , 9, 1/2, 1/3, , 1/9} and -={1,2, ,9,1, 1/2, ,1/9} as the sets from which the pairwise comparison judgments are assigned at random to examine the variation in the values determined for the mean random consistency index. By extensive simulation analysis, we found that both methods produce the same values for the mean random consistency random index. Also, we found that the reason for producing two different sets of values is the use of vs. - and not the selection of the Power Method vs. Saaty's Eigenvector Method.     

分布式并行安全操作系统的用户一致性算法

在基于Linux内核的分布式并行安全操作系统中,由于没有全局一致的用户鉴别和访问权限管理机制,对系统的安全带来危害。该文在对用户权限验证机制进行分析的基础上,给出了由全局同步算法和用户信息一致性协议组成的实现用户一致性的算法。通过测试表明该算法可以有效地保证系统的用户一致性。     

An Estimation Method of the Pair Potential Function for Gibbs Point Processes on Spheres

An estimation method for pairwise interaction potential of a stationary Gibbs point process is introduced by considering the case of observations located on a sphere. It is based both on Fourier decomposition of the potential and on minimum contrast estimation. It is defined when many independent realizations of the process are available. Consistency and asymptotic normality are proved for the resulting estimators. The method enables derivation of the choice of the potential function by embedded hypotheses testing. The method is applied to independent observations of root locations on internodes around stem of maize roots. The internodes are described as circles and we focus on the interaction function associated with the potential. Since a model with too many components seems to fail, we choose a sequential procedure based on embedded hypotheses testing to build a simpler model.     

明代满蒙市场需求及文化、社会组织的相同特点

明代满族和蒙古族有共同的市场需求,与中原汉族地区建立贸易关系是他们的相同目的。满、蒙两族主要用畜产品、渔猎产品、土特产品交换中原汉族的农产品、手工业产品。明代满族和蒙古族人民不仅有很多相同的习俗爱好,而且萨满文化也有许多相同特点。至于满、蒙社会组织的相同特点是人与人、户与户之间的关系,是地缘关系而不是血缘关系。     

The mixed model for survey regression estimation

Estimation of the population mean under the regression model with random components is considered. Conditions under which the random components regression estimator is design consistent are given. It is shown that consistency holds when incorrect values are used for the variance components. The regression estimator constructed with model parameters that differ considerably from the true parameters performed well in a Monte Carlo study. Variance estimators for the regression predictor are suggested. A variance estimator appropriate for estimators constructed with a biased estimator for the between-group variance component performed well in the Monte Carlo study.     

基于流形学习的非一致性判断矩阵排序方法

针对传统层次分析法(AHP)在构造判断矩阵过程中需要满足一致性条件问题,本文研究AHP方法需要进行一致性调整的原因,提出了一种基于流形学习的非一致性判断矩阵排序方法。在非一致性判断矩阵排序过程中,首先基于近邻距离的概念,构建出判断矩阵所对应数据集的近邻距离矩阵;然后以近邻点的线性表示为基础,将每个数据点映射到一个全局低维坐标系,并据此获得判断矩阵所对应的低维嵌入;根据各层求解出的低维嵌入对各层要素进行优劣排序,进而得到最终排序结论。最后,通过数值案例验证了所提方法的有效性和实用性。     

Bridge Estimation for Linear Regression Models with Mixing Properties

Penalized regression methods have for quite some time been a popular choice for addressing challenges in high dimensional data analysis. Despite their popularity, their application to time series data has been limited. This paper concerns bridge penalized methods in a linear regression time series model. We first prove consistency, sparsity and asymptotic normality of bridge estimators under a general mixing model. Next, as a special case of mixing errors, we consider bridge regression with autoregressive and moving average (ARMA) error models and develop a computational algorithm that can simultaneously select important predictors and the orders of ARMA models. Simulated and real data examples demonstrate the effective performance of the proposed algorithm and the improvement over ordinary bridge regression.     

Semiparametric Mixtures of Symmetric Distributions

We consider in this paper the semiparametric mixture of two unknown distributions equal up to a location parameter. The model is said to be semiparametric in the sense that the mixed distribution is not supposed to belong to a parametric family. To insure the identifiability of the model, it is assumed that the mixed distribution is zero symmetric, the model being then defined by the mixing proportion, two location parameters and the probability density function of the mixed distribution. We propose a new class of M‐estimators of these parameters based on a Fourier approach and prove that they are ‐consistent under mild regularity conditions. Their finite sample properties are illustrated by a Monte Carlo study, and a benchmark real dataset is also studied with our method.     

Bayesian ROC curve estimation under binormality using an ordinal category likelihood

Receiver operating characteristic (ROC) curve has been widely used in medical diagnosis. Various methods are proposed to estimate ROC curve parameters under the binormal model. In this paper, we propose a Bayesian estimation method from the continuously distributed data which is constituted by the truth-state-runs in the rank-ordered data. By using an ordinal category data likelihood and following the Metropolis–Hastings (M–H) procedure, we compute the posterior distribution of the binormal parameters, as well as the group boundaries parameters. Simulation studies and real data analysis are conducted to evaluate our Bayesian estimation method.