品类个性的形成与作用机理

现有产品分类法没有反映消费者品类需求的差异,不能很好指导行业营销实践,而品类个性的提出为品类特性研究提供了全新的思路。本研究对影响品类个性形成的因素以及品类个性对品牌个性和品牌传播的影响进行逻辑分析,探索性地提出了解释品类个性形成和作用机理的结构模型。研究表明,消费需要类型、产品物理形式和产品生命周期等3个因素影响了品类个性的形成,所得到的品类个性可采用维度的方法描述。品类个性对品牌个性的选择和品牌传播的设计起指导作用。     

试论白居易闲适诗的分期、内容及艺术特色

本文认为白居易的闲适诗以元和十年诗人被贬江州司马为界 ,分为前后两期。前期多写作者从政之余的悠闲之乐 ,也时杂仕途险恶的忧疑 ;后期多乐天知命、明哲保身之作。他的闲适诗大都诗意含蓄、韵味盎然 ,表现出一种圆熟和自然流丽之美 ,在艺术上达到了很高的成就     

当前我国数据库营销存在的问题及对策

数据库营销在西方发达国家的企业里已相当普及,因为它已成为一个企业在新的时代建立新的竞争优势的有力工具。而在国内,很多企业对数据库营销存在着不同程度的误解甚至完全不知,在我国已经加入WTO、世界经济一体化的今天的确让人担忧。这也是我们对该问题进行分析研究的动因。     

中国海事系统的职位分类管理

通过对中国海事系统的实地调研,运用工作分析和职位分类的理论,分析在中国海事系统职位分类管理中存在的职位分析不到位、职位说明不规范、职位分类不科学、职级设置不合理、职位管理的环境适应性差等问题,提出改进职位分析、岗位设置、职级设计、职位说明书和岗位轮换的思路。     

Bayesian incorporation of repeated measurements in logistic discrimination

A common problem in medical statistics is the discrimination between two groups on the basis of diagnostic information. Information on patient characteristics is used to classify individuals into one of two groups: diseased or disease-free. This classification is often with respect to a particular disease. This discrimination has two probabilistic components: (1) the discrimination is not without error, and (2) in many cases the a priori chance of disease can be estimated. Logistic models (Cox 1970; Anderson 1972) provide methods for incorporating both of these components. The a posteriori probability of disease may be estimated for a patient on the basis of both current measurement of patient characteristics and prior information. The parameters of the logistic model may be estimated on the basis of a calibration trial. In practice, not one but several sets of measurements of one characteristic of the patient may be made on a questionable case. These measurements typically are correlated; they are far from independent. How should these correlated measurements be used? This paper presents a method for incorporating several sets of measurements in the classification of a case.     

毒隐翅虫研究进展 1名称,分类与生物学

本文论及毒隐翅虫的学名、俗名、分类与生物学.该属棣于毒隐翅虫亚科的毒隐翅虫族.     

Criteria for the equality between ordinary least squares and best linear unbiased estimators under certain linear models

A new necessary and sufficient condition is derived for the equality between the ordinary least-squares estimator and the best linear unbiased estimator of the expectation vector in linear models with certain specific design matrices. This condition is then applied to special cases involving one-way and two-way classification models.     

An analysis of two probabilistic model induction techniques

Two probabilistic model induction techniques, cart and constructor, are compared, via a series of experiments, in terms of their ability to induce models that are both interpretable and predictive. The experiments show that, although both algorithms are able to deliver classifiers with predictive performance close to that of the optimal Bayes rule,constructor is able to generate a probabilistic model that is more easily interpretable than the cart model. On the other hand, cart is a more mature algorithm and is capable of handling many more situations (e.g., real-valued training sets) thanconstructor. A variety of characteristics of both algorithms are compared, and suggestions for future research are made.     

A Comment on Ali Tas˛ıran's `Wage and income effects on the timing and spacing of births in Sweden and in the United States'

This note reviews and evaluates Taşıran's (1995) claim that estimated female wage effects on Swedish fertility dynamics reported by Heckman and Walker (1990) are not robust to the use of microwage data. The results reported here indicate that once individual wage measures have been purged of measurement error, estimated female wage effects are not sensitive to the introduction of microwages. The results reported by Heckman and Walker (1990) persist even with the use of microwage data. Received: 8 March 1996/Accepted: 4 December 2001 I thank Tom MaCurdy, Eric French and two anonymous referees for useful comments. This research was supported by NICHD grants HD-19226 and HD-28685. The usual disclaimer applies. Responsible editor: Klaus F. Zimmermann.     

Integer programming formulations of statistical classification problems

A series of approaches is presented to formulate statistical classification problems using integer programming. The formulations attempt to maximize the number of observations that can be properly classified and utilize single function, multiple function and hierarchical multiple function approaches to the problems. The formulations are tested using standard software on a sample problem and new approaches are compared to those of other authors. As the solution of such problems gives rise to various awkward features in an integer programming framework, it is demonstrated that new approaches to formulation will not be completely successful in avoiding the difficulties of existing methods, but demonstrate certain gains.