基于非线性主成分和聚类分析的综合评价方法

针对传统主成分在处理非线性问题上的不足，阐述了传统方法在数据无量纲化中“中心标准化”的缺点和处理“线性”数据时的缺陷，给出了数据无量纲化和处理“非线性”数据时的改进方法，并建立了一种基于“对数中心化”的非线性主成分分析和聚类分析的新的综合评价方法。实验表明，该方法能有效地处理非线性数据。     

论普通话水平测试中异读词的规范问题

普通话水平测试(PSC)中异读词的存在,相当程度上影响了PSC的顺利进行。针对PSC中异读词读音混乱现象,对此类异读词进行系统分类,综合考虑审音标准,提出切实可行的解决办法,有利于确保PSC的科学性、规范性、权威性。     

Bayesian binary segmentation procedure for detecting streakiness in sports

Summary.  When an individual player or team enjoys periods of good form, and when these occur, is a widely observed phenomenon typically called 'streakiness'. It is interesting to assess which team is a streaky team, or who is a streaky player in sports. Such competitors might have a large number of successes during some periods and few or no successes during other periods. Thus, their success rate is not constant over time. We provide a Bayesian binary segmentation procedure for locating changepoints and the associated success rates simultaneously for these competitors. The procedure is based on a series of nested hypothesis tests each using the Bayes factor or the Bayesian information criterion. At each stage, we only need to compare a model with one changepoint with a model based on a constant success rate. Thus, the method circumvents the computational complexity that we would normally face in problems with an unknown number of changepoints. We apply the procedure to data corresponding to sports teams and players from basketball, golf and baseball.     

邓小平“实事求是”思想的当代诠释

邓小平把"一切从实际出发"与"实事求是"并列,这里的"实际"、"实事"要理解为"事实",并且事实具有直接性和可靠性,由此"一切从实际出发"、尊重事实是"实事求是"的出发点。事实包括客体事实和价值事实,价值事实在"实事求是"中更为重要。从价值事实中求"是",这个"是"就集中体现为"三个有利于"标准,"三个有利于"标准是"实事求是"的最终标准。人民利益标准是"三个有利于"标准中的最高标准。由此人民利益标准就成为"实事求是"的最高标准中的核心。人民利益标准既是"实事求是"的最高标准,又是"党的一切执政活动的最高标准",因而就成为中国社会主义现代化建设的最高标准的核心。只有坚持人民利益标准,才能真正实现中华民族的伟大复兴。     

论公司高管职务犯罪行为

职务性是公司高管职务犯罪行为的本质特征;根据不同的划分标准,公司高管职务犯罪行为可以分为几种不同的类型;我国《刑法》对公司高管职务行为的入罪标准作出了不同规定,正确界定公司高管职务犯罪行为与公司犯罪行为之间的区别与联系非常重要。     

民主革命时期毛泽东保护和发展私营经济思想论析

在民主革命时期,毛泽东同志根据中国经济落后的现实国情和中国革命的性质、任务,提出了利用、保护和发展私营经济的思想.这既是对我党历史经验的凝重总结,也是对中国社会政治经济走向的深层思考.这一认识过程的曲折反复也折射出探索中国革命道路的复杂与艰辛.     

An Application of Matrix Power Series to Linear Models

In the system of two seemingly unrelated regressions, employing a matrix power series, we show that the two-stage estimator is better than the ordinary least square estimator (OLSE) in terms of the mean square error matrix (MSEM) criterion. The result enriches the existing literature and can be applied to many fields of applications related to economics and statistics.     

Akaike Information Criterion for Selecting Variables in the Nested Error Regression Model

The Akaike Information Criterion (AIC) is developed for selecting the variables of the nested error regression model where an unobservable random effect is present. Using the idea of decomposing the likelihood into two parts of “within” and “between” analysis of variance, we derive the AIC when the number of groups is large and the ratio of the variances of the random effects and the random errors is an unknown parameter. The proposed AIC is compared, using simulation, with Mallows' C _p , Akaike's AIC, and Sugiura's exact AIC. Based on the rates of selecting the true model, it is shown that the proposed AIC performs better.     

Modeling bivariate survival data using shared inverse Gaussian frailty model

ABSTRACT

The shared frailty models are often used to model heterogeneity in survival analysis. The most common shared frailty model is a model in which hazard function is a product of a random factor (frailty) and the baseline hazard function which is common to all individuals. There are certain assumptions about the baseline distribution and the distribution of frailty. In this paper, we consider inverse Gaussian distribution as frailty distribution and three different baseline distributions, namely the generalized Rayleigh, the weighted exponential, and the extended Weibull distributions. With these three baseline distributions, we propose three different inverse Gaussian shared frailty models. We also compare these models with the models where the above-mentioned distributions are considered without frailty. We develop the Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in these models. We present a simulation study to compare the true values of the parameters with the estimated values. A search of the literature suggests that currently no work has been done for these three baseline distributions with a shared inverse Gaussian frailty so far. We also apply these three models by using a real-life bivariate survival data set of McGilchrist and Aisbett (1991 McGilchrist, C.A., Aisbett, C.W. (1991). Regression with frailty in survival analysis. Biometrics 47:461–466.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) related to the kidney infection data and a better model is suggested for the data using the Bayesian model selection criteria.     

Robust two-level regular fractional factorial designs

Abstract

In this paper, we introduce the concept of model quality for two-level regular fractional factorial designs. Under the effect hierarchy principle, this paper raises the definition of model quality and introduces robust model-number pattern (RP) to choose the optimal robust design. Some theoretical results on this optimality and comparisons with GMC and MEC criterion are given.