Characterizing Relationships Between Estimations Under a General Linear Model with Explicit and Implicit Restrictions by Rank of Matrix

In the investigation of the restricted linear model ? _r  = {y, X β | A β = b, σ² Σ}, the parameter constraints A β = b are often handled by transforming the model into certain implicitly restricted model. Any estimation derived from the explicitly and implicitly restricted models on the vector β and its functions should be equivalent, although the expressions of the estimation under the two models may be different. However, people more likely want to directly compare different expressions of estimations and yield a conclusion on their equivalence by using some algebraic operations on expressions of estimations. In this article, we give some results on equivalence of the well-known OLSEs and BLUEs under the explicitly and implicitly restricted linear models by using some expansion formulas for ranks of matrices.     

一种复杂场景雷达图像实时仿真方法

雷达图像计算机仿真技术是解决多参数雷达图像数据源匮乏的有效途径,其核心是对地表场景电磁物理模型的建模.文中提出了一种利用待仿真场景地物的先验信息和数字高程信息,对待仿真场景进行雷达成像的电磁物理特性建模,进而实现雷达图像仿真的方法.仿真结果表明,该方法可以实时地对地表复杂大场景进行多模式、多参数变化的雷达成像仿真.     

论合成高分子材料与现代社会的互动性

论述了影响合成高分子材料产生与发展的主要社会因素,说明了合成高分子材料在人民生活和经济建设方面对人类现代社会发展的积极作用.     

Discrete distributions and purchasing models

Ihis paper reviews the use of different discrete distributions in the modelling of consumer purchasing behaviour.. A feature of the work is the extensive empirical validation of the models. Some interesting characterizations are briefly discussed.. Ihe paper concludes with some unresolved problems and suggested areas for future research     

优化算法在手征媒质中的应用研究

由于手征媒质的手征参数可调性,使它成为一种新型的吸波材料,在减缩目标雷达散射截面方面有巨大的应用前景.文中运用传输线法分析了金属衬底上涂敷手征媒质的反射特性,计算了手征参数对手征媒质反射特性的影响;然后基于非均匀有理B样条建模,采用物理光学法比较了目标涂敷常规吸波材料与手征媒质时的雷达散射截面,结果说明了手征媒质减小反射电磁波的效果更好;最后运用粒子群算法和模拟退火算法在给定的范围内优化手征参数,并计算了在此参数下目标的散射截面.     

Testing the rate ratio under inverse sampling based on gradient statistic

Inverse sampling is widely applied in studies with dichotomous outcomes, especially when the subjects arrive sequentially or the response of interest is difficult to obtain. In this paper, we investigate the rate ratio test problem under inverse sampling based on gradient statistic with the asymptotic method and parametric bootstrap technique. The gradient statistic has many advantages, for example, it is simple to calculate and competitive with Wald-type, score and likelihood ratio tests in terms of local power. Numerical studies are carried out to evaluate the performance of our gradient test and the existing tests, namely Wald-type, score and likelihood ratio tests. The simulation results suggest that the gradient test based on the parametric bootstrap method has excellent type I error control and large powers even in small sample design. Two real examples, from a heart disease study and a drug comparison study, are applied to illustrate our methods.     

Goodness-of-fit testing strategies from indirect observations

We consider in this paper a goodness-of-fit testing problem in a density framework. In particular, we deal with an error-in-variables model where each new incoming observation is gathered with a random independent error. It is well known that in such a situation, we are faced with an inverse (deconvolution) problem. Nevertheless, following recent results in the Gaussian white noise model, we prove that using procedures containing a deconvolution step is not always necessary.     

基于改进雷达图的网络舆情实例指标体系研究

旨在建立可视化的灵活指标体系。通过比较分析法对现有网络舆情指标体系进行分析,建立相关量化模型。应用“投资组合理论”思想,以占中事件为例,利用其百度、新浪、鹰击系统等相关数据,综合应用现有指标体系,引入改进雷达图工具,最终结合网络舆情指标的特点建立改进雷达图的网络舆情指标体系。     

Characterizations based on regression assumptions of order statistics

Let X₍₁₎≤X₍₂₎≤···≤X_(n) be the order statistics from independent and identically distributed random variables {X_i, 1≤i≤n} with a common absolutely continuous distribution function. In this work, first a new characterization of distributions based on order statistics is presented. Next, we review some conditional expectation properties of order statistics, which can be used to establish some equivalent forms for conditional expectations for sum of random variables based on order statistics. Using these equivalent forms, some known results can be extended immediately.     

Functional calibration estimation by the maximum entropy on the mean principle

We extend the problem of obtaining an estimator for the finite population mean parameter incorporating complete auxiliary information through calibration estimation in survey sampling under a functional data framework. The functional calibration sampling weights of the estimator are obtained by matching the calibration estimation problem with the maximum entropy on the mean – MEM – principle. In particular, the calibration estimation is viewed as an infinite-dimensional linear inverse problem following the structure of the MEM approach. We give a precise theoretical setting and estimate the functional calibration weights assuming, as prior measures, the centred Gaussian and compound Poisson random measures. Additionally, through a simple simulation study, we show that the proposed functional calibration estimator improves its accuracy compared with the Horvitz–Thompson one.