A new financial stress index model based on support vector regression and control chart

Financial stress index (FSI) is considered to be an important risk management tool to quantify financial vulnerabilities. This paper proposes a new framework based on a hybrid classifier model that integrates rough set theory (RST), FSI, support vector regression (SVR) and a control chart to identify stressed periods. First, the RST method is applied to select variables. The outputs are used as input data for FSI–SVR computation. Empirical analysis is conducted based on monthly FSI of the Federal Reserve Bank of Saint Louis from January 1992 to June 2011. A comparison study is performed between FSI based on the principal component analysis and FSI–SVR. A control chart based on FSI–SVR and extreme value theory is proposed to identify the extremely stressed periods. Our approach identified different stressed periods including internet bubble, subprime crisis and actual financial stress episodes, along with the calmest periods, agreeing with those given by Federal Reserve System reports.     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

Response strategy to environment context factors using a lean and agile approach: Implications for firm performance

Based on the environment-strategy performance perspective and dynamic capabilities framework, we develop a theoretical model and hypotheses specifying how supply chain collaboration as a response to environment context factors – competitive intensity, supply uncertainty, technological turbulence and market turbulence, using a lean and agile strategy may influence firm performance. We test the model using partial least square structural equation modelling on data collected from a field survey with responses from 152 manufacturing firms representing a variety of industries. Empirical findings generally support the relationship between collaboration and firm performance using a lean and agile strategy. Also, for firms in industries that face environments characterised by high supply uncertainty and competitive intensity with, technological turbulence, the study finds evidence of a direct relationship between these environmental factors and supply chain collaboration. The findings provide an initial strategic response framework for appropriately aligning a lean and agile supply chain strategy through collaboration with environment context factors to achieve firm performance improvements.     

Acculturative stress in the adjustment of immigrant families

This study reviews the issue of acculturative stress in immigrant families. Acculturative stress includes behaviors experienced by immigrants that are a direct consequence of the process of acculturation and adaptation to a new society. A number of stressors impacting on the acculturation of immigrant families is discussed. These stressors include lack of English language skills, employment and economic status, educational background, family life, and sociopolitical and immigration status.     

Child Characteristics,Parenting Stress,and Parental Involvement: Fathers Versus Mothers

This study examined variations in the relationships among child characteristics, parenting stress, and parental involvement. Participants were 100 two‐parent families with preschool‐aged children. Self‐report and interview data were collected to measure parental involvement, as well as perceptions of child temperament and parental stress. Analyses revealed significant, yet somewhat different, associations between child temperament and parental stress for mothers and fathers. More significant associations were found between perceptions of child temperament and involvement for fathers than for mothers. The associations between child temperament and parental stress and involvement differed on the basis of child and parent gender. Results are discussed in terms of future research on father involvement, as well as programs designed to encourage fathers to assume more active parental roles.     

Integrating Family Resilience and Family Stress Theory

The construct, family resilience, has been defined and applied very differently by those who are primarily clinical practitioners and those who are primarily researchers in the family field. In thisarticle, the family resilience perspective is integrated with conceptual definitions from family stress theory using the Family Adjustment and Adaptation Response (FAAR) Model in an effort to clarify distinctions between family resiliency as capacity and family resilience as a process. The family resilience process is discussed in terms of (a) the meaning of significant risk exposure (vs. the normal challenges of family life) and (b) the importance of making conceptual and operational distinctions between family system outcomes and family protective processes. Recommendations for future family resilience research are discussed.     

Ethnicity, migration and health: A population-based study of 338 refugees from Latin America, 396 nonrefugee immigrants from Finland and 161 from southern Europe and 996 age-, sex- and education-matched controls from Sweden

This article shows the influence of being a refugee from Latin America or a nonrefugee immigrant from southern Europe or Finland on self-reported illness, controlling for social factors and lifestyle. The study population consisted of 338 Latin American refugees, a random sample of 396 Finnish and 161 southern European immigrants and 996 age-, sex- and education-matched Swedish controls. The data were analysed unmatched with logistic regression (multivariate analysis) in main effect models. The strongest independent risk indicator for long-term illness was being a Latin American refugee (estimated odds ratio (OR)=2.96, 95% confidence interval (CI)=2.19–3.82). There was a significant association between being a Latin American refugee and period prevalence, ill health and unsatisfied need for care. Being a southern European or Finnish immigrant was a risk indicator of ill health but was not associated with the other dependent factors. Not feeling secure in daily life was a strong risk indicator for long-term illness and ill health (estimated OR=1.89, 95% CI=1.26–2.76 and OR=3.04, 95% CI= 1.97–4.48) respectively). Being a Latin American refugee was equal in importance to traditional risk factors such as overweight and not taking regular exercise for long-term illness and ill health.     

论我国农村基层民主建设的现实基础

基层民主建设是有中国特色的民主政治内容之一。近年来,我国农村的基层民主建设引起世人关注。本文从我国农村的经济因素、社会因素和文化因素三个方面探讨了在经济、文化相对落后的农村推进民主进程的可能性与可行性。     

Kernel Estimation of Rate Function for Recurrent Event Data

Abstract.  Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce a curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.     

几类全微分方程问题的求解定理

利用全微分方程的条件，给出一类微分方程的积分因子及通解公式，得出一类全微分方程中未知函数所满足的二阶线性微分方程，获得未知函数及全微分方程的通解。