Geometric ergodicity of nonlinear autoregressive models with changing conditional variances

The authors give easy‐to‐check sufficient conditions for the geometric ergodicity and the finiteness of the moments of a random process x_t = ?(x_t‐1,…, x_t‐p) + ?_tσ(x_t‐1,…, x_t‐q) in which ?: R^p → R, σ R^q → R and (?_t) is a sequence of independent and identically distributed random variables. They deduce strong mixing properties for this class of nonlinear autoregressive models with changing conditional variances which includes, among others, the ARCH(p), the AR(p)‐ARCH(p), and the double‐threshold autoregressive models.     

Occupancy numbers for dynamic heterogeneous populations: Estimate of particles lifetimes

A dynamic model of a heterogeneous population is studied. Particles belonging to a population are divided, at every time t, into a finite number of classes according to their types and the partition changes over time. The role of the occupancy numbers, namely the cardinality of each class, is highlighted. The relationship between the stochastic process of occupancy numbers and the process of particle types is analyzed. The main goal of this paper is the estimation of the lifetime of each particle at a given time t, when the observed data are the history of the process of the number of dead particles up to t. Furthermore, a discrete time approximation of the filter is given.     

Comparing relative importance of the same component in a series system in two environments

The relative performance of a component of a series system in two different environments is considered. The conditional probability of the failure of the system due to the failure of the specified component given that the system failed before time t is regarded as a measure of relative importance of the component to the system. A U-statistic test for checking the equality of the relative importance of the component to the system in two different environments against the alternative that the relative importance is smaller in one of the environments, is proposed. Some simulation results for estimating the power of the test are reported. The proposed test is applied to one real data set and it is seen that a different aspect of the data is brought out by this comparison than that by the comparisons of the absolute importance functions such as the subsurvival functions, considered in earlier studies.     

A comparison of classification models to identify the Fragile X Syndrome

The main models of machine learning are briefly reviewed and considered for building a classifier to identify the Fragile X Syndrome (FXS). We have analyzed 172 patients potentially affected by FXS in Andalusia (Spain) and, by means of a DNA test, each member of the data set is known to belong to one of two classes: affected, not affected. The whole predictor set, formed by 40 variables, and a reduced set with only nine predictors significantly associated with the response are considered. Four alternative base classification models have been investigated: logistic regression, classification trees, multilayer perceptron and support vector machines. For both predictor sets, the best accuracy, considering both the mean and the standard deviation of the test error rate, is achieved by the support vector machines, confirming the increasing importance of this learning algorithm. Three ensemble methods - bagging, random forests and boosting - were also considered, amongst which the bagged versions of support vector machines stand out, especially when they are constructed with the reduced set of predictor variables. The analysis of the sensitivity, the specificity and the area under the ROC curve agrees with the main conclusions extracted from the accuracy results. All of these models can be fitted by free R programs.     

Double Sampling Ratio-product Estimator of a Finite Population Mean in Sample Surveys

It is well known that two-phase (or double) sampling is of significant use in practice when the population parameter(s) (say, population mean X¯) of the auxiliary variate x is not known. Keeping this in view, we have suggested a class of ratio-product estimators in two-phase sampling with its properties. The asymptotically optimum estimators (AOEs) in the class are identified in two different cases with their variances. Conditions for the proposed estimator to be more efficient than the two-phase sampling ratio, product and mean per unit estimator are investigated. Comparison with single phase sampling is also discussed. An empirical study is carried out to demonstrate the efficiency of the suggested estimator over conventional estimators.     

叶嘉莹词学理论新框架初探

西方文学理论的特点在于研究的系统性与解剖的深入性，而中国古代文学理论的特点则在于对整体生命的把握。二者各有其优点和不足。叶嘉莹教授把这二者完美地结合起来，在词学研究中开辟出一条新的道路，使许多有争论的问题迎刃而解。文章对叶嘉莹的词学理论新框架进行了初步的探索，指出其最大特点是把古代与当代沟通起来，使古典作品在现代人心灵中得到生命的延续。这正是叶嘉莹词学理论体系的意义与价值之所在。     

摄影艺术美学断想

纪实美是摄影艺术独具的美学品格。但是 ,纪实性只是艺术创作的手段和方法。摄影艺术是“心”与“物”的结合 ,“情”与“景”的结合。摄影艺术的真实是“双重的真实”。典型化是一切艺术美的核心 ,也是摄影艺术美的核心。摄影艺术典型化的基本方法是选择。决定摄影艺术美的 ,还在于摄影作品要有形式美。摄影艺术的形式美有特有的组合材料 ,具有独特的审美价值     

浅谈“双师型”教师队伍建设

随着社会主义市场经济的发展,市场竞争越来越激烈,各行各业对高素质人才的需求越来越迫切,如何培养出高素质复合型人才,成为目前职业学校的首要任务。为提高教学质量,需要打造一支技术过硬“双师型”的教师队伍,本文就“双师型”教师队伍的建设的意义和措施进行了探讨。     

社会学方法的新规则——安东尼·吉登斯对解释社会学的三次超越

吉登斯建构社会学方法的新规则是通过对解释社会学的批判性超越而实现的,这种批判性超越主要体现在三个方面,即吉登斯澄清了行动的概念以及行动与目的、理由和动机的关系;将行动理论与对制度结构的性质分析联系在一起;解决任何试图阐明社会科学方法的逻辑都会遭遇的认识论难题。