Limited information bayesian analysis of a structural coefficient in a simultaneous equations system

An analytical expression is obtained for the marginal posterior density for a structural coefficient in a simultaneous equations system based on a limited information Bayesian analysis. A con- ditional posterior density is obtained given reduced form para- meters. This conditional posterior density is in univariate student t form. Numerical examples suggest that the conditional density hasa tighter distribution around the posterior mean than the unconditional density when the correlation between the endo- genous variables and the structural error term is high.     

Reconsideration of the F-test of the analysis of variance: the semi-bayesian significance test

The usual F-test of the analysis of variance is reconsidered within the Bayesian framework, In terms of predictive distributions, This leads to the notion of semi-Bayesian significance test, so called because it consists in only probabilizing the space of nuisance parameters, thus bringing a general principle for “eliminating” nuisance parameters, or more exactly incorporating information about these parameters. The approach is shown to extend the F-tests, by allowing the testing of hypotheses of non-zero effects.     

On regression modelling with dummy variables versus separate regressions per group: Comment on Holgersson et al.

In a recent issue of this journal, Holgersson et al. [Dummy variables vs. category-wise models, J. Appl. Stat. 41(2) (2014), pp. 233–241, doi:10.1080/02664763.2013.838665] compared the use of dummy coding in regression analysis to the use of category-wise models (i.e. estimating separate regression models for each group) with respect to estimating and testing group differences in intercept and in slope. They presented three objections against the use of dummy variables in a single regression equation, which could be overcome by the category-wise approach. In this note, I first comment on each of these three objections and next draw attention to some other issues in comparing these two approaches. This commentary further clarifies the differences and similarities between dummy variable and category-wise approaches.     

Difference-based Methods for Truncating the Singular Value Decomposition

Given a noisy time series (or signal), one may wish to remove the noise from the observed series. Assuming that the noise-free series lies in some low-dimensional subspace of rank r, a common approach is to embed the noisy time series into a Hankel trajectory matrix. The singular value decomposition is then used to deconstruct the Hankel matrix into a sum of rank-one components. We wish to demonstrate that there may be some potential in using difference-based methods of the observed series in order to provide guidance regarding the separation of the noise from the signal, and to estimate the rank of the low-dimensional subspace in which the true signal is assumed to lie.     

Multivariate Approach for Comparative Evaluations of Customer Satisfaction with Application to Transport Services

In problems related to evaluations of products or services (e.g. in customer satisfaction analysis) the main difficulties concern the synthesis of the information, which is necessary for the presence of several evaluators and many response variables (aspects under evaluation). In this article, the problem of determining and comparing the satisfaction of different groups of customers, in the presence of multivariate response variables and using the results of pairwise comparisons is addressed. Within the framework of group ranking methods and multi criteria decision making theory, a new approach, based on nonparametric techniques, for evaluating group satisfaction in a multivariate framework is proposed and the concept of Multivariate Relative Satisfaction is defined. An application to the evaluation of public transport services, like the railway service and the urban bus service, by students of the University of Ferrara (Italy) is also discussed.     

中小企业技术创新研究

中小企业已成为推动我国社会经济发展的重要力量。但是从整体来看,技术创新能力不强严重制约了中小企业的发展,这需要运用多种措施来予以解决。首先从存在的问题着手,分析了中小企业技术创新的风险,最后根据我国中小企业所面临的实际情况给出了一些具体的有针对性的对策。     

Analysis of all-zero binomial outcomes with borderline and equilibrium priors

This article is concerned with the analysis of a random sample from a binomial distribution when all the outcomes are zero (or unity). We discuss how elicitation of the prior can be reduced to asking the expert whether (and which of) the so-called borderline or equilibrium priors are plausible.     

基于洛特卡定律的国际社会化媒体研究成熟度分析

移动智能终端的不断升级和各种互联网技术的融合发展给社会化媒体产业带来了巨大的增长空间,近年来社会化媒体研究也随之成为最具增长力的学科领域之一。经典洛特卡定律能揭示特定研究领域作者数与所著科学文献数之间的规律,常被用来评判特定研究领域的发展成熟度,但存在精度不够等问题。在经典洛特卡定律的基础上,结合国际社会化媒体研究领域最新发展,拟合出该领域洛特卡定律常数的非线性回归方法来提高计算精度:以1994—2013年间ISI Web of Science数据库中社会化媒体相关主题的8 021篇文献为研究样本(SSCI数据库文献4 501篇,SCI数据库的文献4 279篇)展开研究,并进行K-S一致性检验。统计分析结果表明:国际社会化媒体领域的研究虽处于快速发展阶段,但成熟度不高,核心作者群尚未达到稳定状态。