A general long-term aging model with different underlying activation mechanisms: Modeling,Bayesian estimation,and case influence diagnostics

In this paper we propose a general cure rate aging model. Our approach enables different underlying activation mechanisms which lead to the event of interest. The number of competing causes of the event of interest is assumed to follow a logarithmic distribution. The model is parameterized in terms of the cured fraction which is then linked to covariates. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis for the proposed model. Moreover, some discussions on the model selection to compare the fitted models are given, as well as case deletion influence diagnostics are developed for the joint posterior distribution based on the ψ-divergence, which has several divergence measures as particular cases, such as the Kullback–Leibler (K-L), J-distance, L₁ norm, and χ²-square divergence measures. Simulation studies are performed and experimental results are illustrated based on a real malignant melanoma data.     

Monitoring means and covariances of multivariate non linear time series with heavy tails

In this paper, the focus is on sequential analysis of multivariate financial time series with heavy tails. The mean vector and the covariance matrix of multivariate non linear models are simultaneously monitored by modifying conventional control charts to identify structural changes in the data. The considered target process is a constant conditional correlation model (cf. Bollerslev, 1990 Bollerslev, T. (1990). Modeling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. Rev. Econ. Stat. 72:498–505.[Crossref], [Web of Science ®] , [Google Scholar]), an extended constant conditional correlation model (cf. He and Teräsvirta, 2004 He, C., Teräsvirta, T. (2004). An extended constant conditional correlation GARCH model and its fourth-moment structure. Economet. Theory 20:904–926.[Crossref], [Web of Science ®] , [Google Scholar]), a dynamic conditional correlation model (cf. Engle, 2002 Engle, R.F. (2002). Dynamic conditional correlation: A simple class of multivariate GARCH models. J. Bus. Econ. Stat. 20(3):339–350.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), or a generalized dynamic conditional correlation model (cf. Capiello et al., 2006 Capiello, L., Engle, R., Sheppard, K. (2006). Asymmetric correlations in the dynamics of global equity and bond returns. J. Financial Economet. 4(4):537–572.[Crossref] , [Google Scholar]). For statistical surveillance we use control charts based on residuals. Further, the procedures are constructed for t-distribution. The detection speed of these charts is compared via Monte Carlo simulation. In the empirical study, the procedure with the best performance is applied to log-returns of the stock market indices FTSE and CAC.     

Testing homogeneity in semiparametric mixture case–control models

Parametric and semiparametric mixture models have been widely used in applications from many areas, and it is often of interest to test the homogeneity in these models. However, hypothesis testing is non standard due to the fact that several regularity conditions do not hold under the null hypothesis. We consider a semiparametric mixture case–control model, in the sense that the density ratio of two distributions is assumed to be of an exponential form, while the baseline density is unspecified. This model was first considered by Qin and Liang (2011 Qin, J., Liang, K.Y. (2011). Hypothesis testing in a mixture case–control model. Biometrics 67(1):182–198.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar], biometrics), and they proposed a modified score statistic for testing homogeneity. In this article, we consider alternative testing procedures based on supremum statistics, which could improve power against certain types of alternatives. We demonstrate the connection and comparison among the proposed and existing approaches. In addition, we provide a unified theoretical justification of the supremum test and other existing test statistics from an empirical likelihood perspective. The finite-sample performance of the supremum test statistics was evaluated in simulation studies.     

Bayesian quantile regression for skew-normal linear mixed models

Linear mixed models have been widely used to analyze repeated measures data which arise in many studies. In most applications, it is assumed that both the random effects and the within-subjects errors are normally distributed. This can be extremely restrictive, obscuring important features of within-and among-subject variations. Here, quantile regression in the Bayesian framework for the linear mixed models is described to carry out the robust inferences. We also relax the normality assumption for the random effects by using a multivariate skew-normal distribution, which includes the normal ones as a special case and provides robust estimation in the linear mixed models. For posterior inference, we propose a Gibbs sampling algorithm based on a mixture representation of the asymmetric Laplace distribution and multivariate skew-normal distribution. The procedures are demonstrated by both simulated and real data examples.     

Dialogic communication in the health care context: A case study of Kaiser Permanente's social media practices

This case study examines how one of the largest not-for-profit health care organizations in the US, Kaiser Permanente, uses social media to communicate with its stakeholders. Through content analysis and interviews, this study identifies the communication models reflected in a sample of social media posts and examines the organization's approach to using social media. The study finds evidence of both one-way and two-way communication models, as well as principles of dialogic communication. The implications of these findings are discussed.     

Disaster response on September 11, 2001 through the lens of statistical network analysis

The rescue and relief operations triggered by the September 11, 2001 attacks on the World Trade Center in New York City demanded collaboration among hundreds of organisations. To shed light on the response to the September 11, 2001 attacks and help to plan and prepare the response to future disasters, we study the inter-organisational network that emerged in response to the attacks. Studying the inter-organisational network can help to shed light on (1) whether some organisations dominated the inter-organisational network and facilitated communication and coordination of the disaster response; (2) whether the dominating organisations were supposed to coordinate disaster response or emerged as coordinators in the wake of the disaster; and (3) the degree of network redundancy and sensitivity of the inter-organisational network to disturbances following the initial disaster. We introduce a Bayesian framework which can answer the substantive questions of interest while being as simple and parsimonious as possible. The framework allows organisations to have varying propensities to collaborate, while taking covariates into account, and allows to assess whether the inter-organisational network had network redundancy—in the form of transitivity—by using a test which may be regarded as a Bayesian score test. We discuss implications in terms of disaster management.     

How Can Low‐income Countries Gain from a Framework Agreement on Climate Change? An Analysis with Integrated Assessment Modelling

By using the integrated assessment model RICE this article carries out a scenario analysis with different assumptions about international negotiations on climate change, in particular hypothesising about reduction in targets for greenhouse gas emissions, technology transfers and financial transfer programmes. It finds that, in terms of growth, developing countries and in particular sub‐Saharan Africa will benefit from agreements that reduce the level of pollution and promote technological diffusion. Moreover, when developed countries are subject to emissions limits and poor regions have no such commitments, financial transfers from rich to developing countries for adaptation and mitigation enhance pro‐poor growth and help the effectiveness of poor countries in reducing emissions.     

禅宗“斗机锋”交际的核心思维模式

“斗机锋”在行为表层体现为双人或多人参与的言语、副言语互动交际。“斗机锋”与一般交际行为存在共性,同时也存在显著差异。“斗机锋”是由禅宗逻辑下的思维系统驱动的,在一般理性下显得不可理喻。“斗机锋”展现出令人眼花缭乱的互动,若剥离其行为表层,则可还原为不同思维模式之间的对垒,涉及的思维模式主要有五类：“一切现成”思维、“不二”思维、“究竟本缘”思维、“离杀”思维、“空空”思维。“斗机锋”训练的基本目标是消除参与者对固化思维程式的执著,开发更广泛的思维途径。经过训练,参与者可以提升思维的创造性、灵活性和迅捷性,也可能被偶然地诱导发生顿悟。     

一般本科院校人才培养目标与培养模式研究

文章通过对高等学校分类、定位的介绍，提出了一般本科院校的人才培养目标应根据社会的需求和学生的差异而多元化，即以应用型、复合型为主体，以研究型为激励，以技能型为补充。按照强化基础、拓宽专业、突出能力、注重创新、提高素质、全面发展的模式实施人才培养。