Strong consistency of the regularized least-squares estimates of infinite autoregressive models

Our main interest is on-line parameter estimation of infinite AR models with exponentially decaying coefficients. The practical importance of the problem follows from the fact that the class of such models includes (but not limited to) all causal invertible ARMA(p,q$p,q$) models. On-line parameter estimation means that the length of the observed data sample is not known a priori and may indefinitely increase. Hence, the parameter estimates should be refined upon arrival of every new observation. So use of the maximum likelihood (ML) method is not feasible due to the high computational burden, and recursive estimation procedures are preferable.     

Strong consistency of non parametric kernel regression estimator for strong mixing samples

For α-mixing samples, we study Priestley–Chao kernel estimator for non parametric regression model. By using the moment inequality and the exponential inequality, the strong consistency and the uniformly strong consistency of the estimator are obtained for some weak conditions.     

Complete consistency for the estimator of nonparametric regression model based on martingale difference errors

Abstract

In this paper, we study the complete consistency for the estimator of nonparametric regression model based on martingale difference errors, and obtain the convergence rates of the complete consistency by using the inequalities for martingale difference sequence. Finally, some simulations are illustrated.     

SMALL AREA ESTIMATION USING SURVEY WEIGHTS WITH FUNCTIONAL MEASUREMENT ERROR IN THE COVARIATE

Nested error linear regression models using survey weights have been studied in small area estimation to obtain efficient model‐based and design‐consistent estimators of small area means. The covariates in these nested error linear regression models are not subject to measurement errors. In practical applications, however, there are many situations in which the covariates are subject to measurement errors. In this paper, we develop a nested error linear regression model with an area‐level covariate subject to functional measurement error. In particular, we propose a pseudo‐empirical Bayes (PEB) predictor to estimate small area means. This predictor borrows strength across areas through the model and makes use of the survey weights to preserve the design consistency as the area sample size increases. We also employ a jackknife method to estimate the mean squared prediction error (MSPE) of the PEB predictor. Finally, we report the results of a simulation study on the performance of our PEB predictor and associated jackknife MSPE estimator.     

自动化学科综合性课程的研究与设置

阐述了一个能够连接自动化学科各个专业单课知识的综合性课程,基于这个课程的教学,使学生能够真正建立系统的专业知识体系,并通过随后的综合实验、实习参观、电气电控实践和毕业设计,使学生建立专业性的“工作经验”。     

A Simple Tool for Qualitatively Testing,Quantitatively Measuring,and Normatively Justifying Savage's Subjective Expected Utility

This paper introduces a new preference condition that can be used to justify (or criticize) expected utility. The approach taken in this paper is an alternative to Savage's, and is accessible to readers without a mathematical background. It is based on a method for deriving comparisons of tradeoffs from ordinal preferences. Our condition simplifies previously-published tradeoff conditions, and at the same time provides more general and more powerful tools to specialists. The condition is more closely related to empirical methods for measuring utility than its predecessors. It provides a unifying tool for qualitatively testing, quantitatively measuring, and normatively justifying expected utility.     

社会人口学特征对农村贫困者自我和谐的预测作用

构建社会主义和谐社会的关键在“人”的和谐。本研究以970名农村贫困者为研究对象,采用自我和谐问卷研究贫困者的 自我和谐度及与其社会人口学特征的关系。研究结果表明：（1）贫困者自身、家庭和社会因素与自我和谐均存在一定程度的相 关关系;（2）贫困者的年龄、文化程度、健康状况、代际贫困、贫困程度、家庭规模收入来源等变量以及年龄与文化程度、家庭规 模与贫困程度等变量的交互作用在自我和谐的三个因素上存在不同程度的显著性差异;（3）贫困者的文化程度、健康状况和家 庭规模变量对自我和谐具有正向预测作用。     

Combining information from multiple surveys through the empirical likelihood method

It is often desirable to combine information collected in compatible multiple surveys in order to improve estimation and meet consistency requirements. Zieschang (1990) and Renssen & Nieuwenbroek (1997) suggested to this end the use of the generalized regression estimator with enlarged number of auxiliary variables. Unfortunately, adjusted weights associated with their approach can be negative. The author uses the notion of pseudo empirical likelihood to construct new estimators that are consistent, efficient and possess other attractive properties. The proposed approach is asymptotically equivalent to the earlier one, but it has clear maximum likelihood interpretations and its adjusted weights are always positive. The author also provides efficient algorithms for computing his estimators.     

An efficiency result for the empirical characteristic function in stationary time-series models

It is shown under general conditions that arbitrarily high asymptotic efficiencies can be obtained when the parameters of a stationary time series are estimated by fitting the characteristic functions of the process to their empirical versions. A consistency and a central limit result are also given.     

民国初年林政兴起和衰落的原因探析

民国初年，自然与社会多方面的因素促成了林政兴旺的局面。然而好景不长，兴林热潮持续了10年左右便衰退下去，当时颁布的一些法规政策的效果也并不明显。经费缺乏、政局混乱、战争破坏、官僚垄断和林权丧失都造成了兴林举措无法实施或收效不大。可见，一个稳定的政治环境及政策的连续性，对社会的可持续发展是至关重要的。民国初年的林政史给我们留下了惨痛的教训。