Model-Based Classification via Mixtures of Multivariate t-Factor Analyzers

A model-based classification technique is developed, based on mixtures of multivariate t-factor analyzers. Specifically, two related mixture models are developed and their classification efficacy studied. An AECM algorithm is used for parameter estimation, and convergence of these algorithms is determined using Aitken's acceleration. Two different techniques are proposed for model selection: the BIC and the ICL. Our classification technique is applied to data on red wine samples from Italy and to fatty acid measurements on Italian olive oils. These results are discussed and compared to more established classification techniques; under this comparison, our mixture models give excellent classification performance.     

分级培养模式下有效教学探析

本文探讨了大众化教育阶段高校实施分级教学的教育学和心理学理论依据，指出了实施分级教学的重要性和必要性，提出了分级教学应遵循的五个原则。阐述了有效教学的教学理念和含义。并以某大学为例，论述了在分级培养模式下进行高等数学有效教学的教学情境设计与实施方法。     

论刑事证据的法律分类

本文对刑事证据的“种类”、“分类”之称谓进行辨析,认为两者实质含义一致,进而提出采 用“法律上的分类”与“理论上的分类”的观点。作者立足我国刑事证据的立法分类,分析其规定不足, 建议重新分类,特别指出刑事证据分类应注视一、二审的转化问题和与今后将建立的证据规则相衔接 问题。     

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously.

In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems.     

Banking on fewer children: financial intermediation,fertility and economic development

This paper shows that financial intermediation can influence fertility and labor allocation decisions by raising market wages. The increase in wages induces some households to abandon “traditional” labor intensive methods of production managed at the household level and supply labor to “modern” sector firms. Since it is optimal for households in the modern sector to have fewer children, the labor allocation decision leads to lower national fertility. A panel VAR using financial intermediation, fertility and industrial employment share data in 87 countries is estimated. The empirical results show that the data are consistent with the theoretical predictions. Received: 20 October 1997/Accepted: 31 August 1998     

Risk attitudes and risky behavior

In economic theory, risk aversion is a characteristic of the typical utility function of money. Observations of how people deal with risks in real life have cast some doubts on the prevalence of risk aversion. People buy insurance, but they also gamble and take investment risks. Many of the conclusions in the discussions of utility derive from experiments employing some kind of lottery choices. While the experiments have given interesting ideas for theory, there has been little testing of the extent to which the obtained measures of risk attitudes correlate with actual behavior. Data from the VSB panel were used to answer three questions: (1) Can hypothetical risky choice questions be meaningfully answered by ordinary survey respondents? (2) What are the relationships between different measures of risk attitudes and actual portfolio choices of risky assets? (3) What is the relationship between risk attitude and playing in lotteries, lotto, etc.?     

唐代小说作者类属分析

唐代 ,是“始有意为小说”的时期。受当时“尚奇好异”思想影响 ,人们乐于创作、编辑、传播小说 ,从而促成了唐代小说的空前繁荣。唐代小说不但质高量丰 ,且多署有作者真实姓名 (或不难考定姓名 ) ,这与古代其他时期的情形大不相同。以唐代小说作者为对象、以其“身份”、“类属”为范围作一梳理 ,从中可见唐人小说繁荣因缘根基之一斑。     

Convexity-based clustering criteria: theory,algorithms, and applications in statistics

This paper deals with the construction of optimum partitions of for a clustering criterion which is based on a convex function of the class centroids as a generalization of the classical SSQ clustering criterion for n data points. We formulate a dual optimality problem involving two sets of variables and derive a maximum-support-plane (MSP) algorithm for constructing a (sub-)optimum partition as a generalized k-means algorithm. We present various modifications of the basic criterion and describe the corresponding MSP algorithm. It is shown that the method can also be used for solving optimality problems in classical statistics (maximizing Csiszárs -divergence) and for simultaneous classification of the rows and columns of a contingency table.     

城乡居民收入差距不合理因素分析及对策

城镇居民和农村居民的收入差距发生了本质变化城乡居民的显性收入差距不能确切反映实际收入差距;差距悬殊而且存在着非自然差距;超过了世界各国相同阶段所固有的水平;收入差距处在倒"U"型曲线的上升阶段.为缩小城乡居民收入差距,必须增加土地投资;保护和提高农民生产的积极性;进行农业产业结构调整;优化农村政策结构;发展教育,培养专业技术人才,加快贫困地区文化、技术和制度等资源开发;实现农业劳动力半转移.     

Conditional Generalized Liouville Distributions on the Simplex

Liouville and generalized Liouville distributions on the simplex have been proposed for modeling compositional data and have been shown to be free from the extreme independence structure that characterizes the Dirichlet class. In this article, generalized Liouville distributions are shown to be rich enough to distinguish some lesser modes of independence as well. Unfortunately, it is noted that the applicability of the Liouville family will be limited, owing to the lack of invariance with respect to the chosen fill-up value. As an alternative, a new family of simplex distributions is proposed, one that admits invariance with respect to choice of fill-up value, as well as the ability to differentiate among many forms of independence.