Bayesian Treatment of Model Uncertainty for Partially Applicable Models

This article discusses how analyst's or expert's beliefs on the credibility and quality of models can be assessed and incorporated into the uncertainty assessment of an unknown of interest. The proposed methodology is a specialization of the Bayesian framework for the assessment of model uncertainty presented in an earlier paper. This formalism treats models as sources of information in assessing the uncertainty of an unknown, and it allows the use of predictions from multiple models as well as experimental validation data about the models’ performances. In this article, the methodology is extended to incorporate additional types of information about the model, namely, subjective information in terms of credibility of the model and its applicability when it is used outside its intended domain of application. An example in the context of fire risk modeling is also provided.     

我国企业品牌定位的五层次研究

近年来中国企业的品牌建设取得了可喜的成绩,出现了许多优秀品牌,这些品牌凭借独特、合适的定位取得了成功。但企业在品牌定位方面存在许多误区,如把品牌定位看作产品定位、品牌定位模糊,缺乏差异性和明确的核心价值、品牌盲目延伸导致定位混淆等问题。因此,产品品牌定位必须树立正确的定位理念,应用正确的品牌定位方法。正确的品牌定位方法可分为产品特征定位、物质利益定位、情感利益定位、个性定位以及价值观定位共五个层次。     

能源安全体系建构的理论与实践

在我国能源安全面临的一系列重大问题中，能源领域的政策规划薄弱，法律保障制度建设与管理体制改革滞后，能源供应与能源安全保障体系缺乏相关政策、法律和制度的保障。只有真正做到政策、法律和管理体制“三位一体”，才能确保国家能源安全。本文从能源安全体系建构的理论和实践出发，借鉴西方能源安全战略实践，从政策、法律和管理体制等角度，对我国能源安全体系的内在机制建构进行分析，旨在为我国与中东能源合作提供借鉴与参考。     

浅论近代青海女性社会地位变迁及其原因

近代是青海女性社会地位发生变迁的时期,本文从女性形体观的转变、女性教育等方面,论述了近代青海女性社会地位的变迁及其原因。     

唐宋时期回族先民对西北商业经济的开发与贡献

重视商业经济,是伊斯兰教的特点之一。唐宋时期,伴随着伊斯兰教的传入,回族先民对西北商业经济进行了开发。他们一方面继承了阿拉伯商业的传统,另一方面在新的环境下,又有所创新、有所发展。在长期不断的开发中,为西北区域经济的繁荣与发展,做出了重要的贡献。     

A nonparametric hypothesis test for heteroscedasticity

In this paper, a hypothesis test for heteroscedasticity is proposed in a nonparametric regression model. The test statistic, which uses the residuals from a nonparametric fit of the mean function, is based on an adaptation of the well-known Levene's test. Using the recent theory for analysis of variance when the number of factor levels goes to infinity, the asymptotic distribution of the test statistic is established under the null hypothesis of homocedasticity and under local alternatives. Simulations suggest that the proposed test performs well in several situations, especially when the variance is a nonlinear function of the predictor.     

State transition modeling of complex monitored health data

This article considers the analysis of complex monitored health data, where often one or several signals are reflecting the current health status that can be represented by a finite number of states, in addition to a set of covariates. In particular, we consider a novel application of a non-parametric state intensity regression method in order to study time-dependent effects of covariates on the state transition intensities. The method can handle baseline, time varying as well as dynamic covariates. Because of the non-parametric nature, the method can handle different data types and challenges under minimal assumptions. If the signal that is reflecting the current health status is of continuous nature, we propose the application of a weighted median and a hysteresis filter as data pre-processing steps in order to facilitate robust analysis. In intensity regression, covariates can be aggregated by a suitable functional form over a time history window. We propose to study the estimated cumulative regression parameters for different choices of the time history window in order to investigate short- and long-term effects of the given covariates. The proposed framework is discussed and applied to resuscitation data of newborns collected in Tanzania.     

Bayesian t-tests for correlations and partial correlations

In this paper, we develop Bayes factor based testing procedures for the presence of a correlation or a partial correlation. The proposed Bayesian tests are obtained by restricting the class of the alternative hypotheses to maximize the probability of rejecting the null hypothesis when the Bayes factor is larger than a specified threshold. It turns out that they depend simply on the frequentist t-statistics with the associated critical values and can thus be easily calculated by using a spreadsheet in Excel and in fact by just adding one more step after one has performed the frequentist correlation tests. In addition, they are able to yield an identical decision with the frequentist paradigm, provided that the evidence threshold of the Bayesian tests is determined by the significance level of the frequentist paradigm. We illustrate the performance of the proposed procedures through simulated and real-data examples.