Incremental Sampling Methodology: Applications for Background Screening Assessments

This article presents the findings from a numerical simulation study that was conducted to evaluate the performance of alternative statistical analysis methods for background screening assessments when data sets are generated with incremental sampling methods (ISMs). A wide range of background and site conditions are represented in order to test different ISM sampling designs. Both hypothesis tests and upper tolerance limit (UTL) screening methods were implemented following U.S. Environmental Protection Agency (USEPA) guidance for specifying error rates. The simulations show that hypothesis testing using two‐sample t ‐tests can meet standard performance criteria under a wide range of conditions, even with relatively small sample sizes. Key factors that affect the performance include unequal population variances and small absolute differences in population means. UTL methods are generally not recommended due to conceptual limitations in the technique when applied to ISM data sets from single decision units and due to insufficient power given standard statistical sample sizes from ISM.     

Assessing respondent-driven sampling: A simulation study across different networks

The purpose was to assess RDS estimators in populations simulated with diverse connectivity characteristics, incorporating the putative influence of misreported degrees and transmission processes. Four populations were simulated using different random graph models. Each population was “infected” using four different transmission processes. From each combination of population x transmission, one thousand samples were obtained using a RDS-like sampling strategy. Three estimators were used to predict the population-level prevalence of the “infection”. Several types of misreported degrees were simulated. Also, samples were generated using the standard random sampling method and the respective prevalence estimates, using the classical frequentist estimator. Estimation biases in relation to population parameters were assessed, as well as the variance. Variability was associated with the connectivity characteristics of each simulated population. Clustered populations yield greater variability and no RDS-based strategy could address the estimation biases. Misreporting degrees had modest effects, especially when RDS estimators were used. The best results for RDS-based samples were observed when the “infection” was randomly attributed, without any relation with the underlying network structure.     

习近平新时代观的理论生成探讨

理顺习近平关于“中国特色社会主义进入新时代”的逻辑理路，有助于系统论证“新时代”的科学性和理论性。从方法论上看，习近平新时代观是应用马克思主义立场观点和方法得出的正确结论。从理论归因看，中国社会主要矛盾的转化作为习近平新时代观生成的主要标志，源于马克思主义关于矛盾运动的基本理论。从理论定位看，习近平新时代观展现的是中国发展的特殊阶段，内含着中国对自身发展的时代定位与目标趋向，渗透着中国与世界在共同发展中的新阶段、新高度、新未来，是对中国发展方向的顶层设计。     

Optimal asset allocation for participating contracts with mortality risk under minimum guarantee

Abstract

We investigate an optimal investment problem of participating insurance contracts with mortality risk under minimum guarantee. The insurer aims to maximize the expected utility of the terminal payoff. Due to its piecewise payoff structure, this optimization problem is a non-concave utility maximization problem. We adopt a concavification technique and a Lagrange dual method to solve the problem and derive the representations of the optimal wealth process and trading strategies. We also carry out some numerical analysis to show how the portfolio insurance constraint impacts the optimal terminal wealth.     

On a class exhibiting trend change in average failure rate

Abstract

Weak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984 Loh, W. Y. 1984. A new generalization of the class of NBU distributions. IEEE Transactions on Reliability R-33 :97–113[Crossref], [Web of Science ®] , [Google Scholar])). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class.     

Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the MCMC typically operates on the hyperparameters, and the subsequent weighting may be based on IS or sequential Monte Carlo (SMC), but allows for multilevel techniques as well. The IS approach provides a natural alternative to delayed acceptance (DA) pseudo-marginal/particle MCMC, and has many advantages over DA, including a straightforward parallelization and additional flexibility in MCMC implementation. We detail minimal conditions which ensure strong consistency of the suggested estimators, and provide central limit theorems with expressions for asymptotic variances. We demonstrate how our method can make use of SMC in the state space models context, using Laplace approximations and time-discretized diffusions. Our experimental results are promising and show that the IS-type approach can provide substantial gains relative to an analogous DA scheme, and is often competitive even without parallelization.     

Structural Change Monitoring for Random Coefficient Autoregressive Time Series

A monitoring scheme is proposed to sequentially detect a structural change in random coefficient autoregressive time series of order p (RCA(p)) after a training period of size T. It extends structural change monitoring to RCA(p) time series. The asymptotic properties of our monitoring statistic are established under both the null of no change in parameters and the alternative of a change in coefficient. The finite sample properties are investigated by a simulation study.     

植入式教学法在大学生职业生涯规划课中的应用

大学生职业生涯规划课是一门集理论型、实践型、经验型为一体的综合性课程。在课堂教学中，通过背景知识、色彩图案、哲理案例、互动体验的植入，充实优化教学内容，增强课程吸引力，激发学生的学习兴趣。通过探索启迪学生思想、更新学习观念以及差异化职业能力培养的教学方法，满足学生的个性化职业规划学习需求。     

双波长比值法测定水杨酸、间苯二酚、对氨基苯甲酸的含量

依据水杨酸、间苯二酚、对氨基苯甲酸三组分的比值光谱特征,以对氨基苯甲酸为干扰组分,选择241nm、278nm作为测定水杨酸的波长;以水杨酸作为干扰组分,选择214nm、240nm作为测定间苯二酚的波长;以间苯二酚作为干扰组分,选择222nm、279nm作为测定对氨基苯甲酸的波长.结果显示,水杨酸浓度在1~80mg/L,基本二酚浓度在0.8~40mg/L,对氨基苯甲酸浓度在0.4~40mg/L范围内具有良好的线性关系.本方法具有测定波长少,光谱分离能力强、计算简单、能在低档分光光度计上实现、易于推广等特点.     

Understanding cultural singularities of ‘Indianness’ in an intercultural business setting

Analysing data from the Indian information technology (IT) industry, this paper advances an understanding of cultural singularities of ‘Indianness’. The research context of an intercultural meeting place of IT and business process outsourcing firms’ overseas subsidiaries, Belgium in this case, allows the authors to identify 10 cultural singularities that typify ‘Indianness’. This ethnographic, reflexive study is further validated by employing Ghoshal's ‘smell of the place’ metaphor through the authors collective experiences as consultants and researchers, and builds and extends upon the popular cultural dimension frameworks for understanding intercultural business and management. Existing cultural dimensions do not sufficiently describe the contemporary intercultural dynamics that typically take place in workplaces, especially so in offshore and outsourcing environments. A provisional set of parameters for understanding Indian culture, with its relevant impact on business life (customs and manners), business processes and business deliverables are proposed in this study.