Moment‐Independent Sensitivity Analysis Using Copula

In risk assessment, the moment‐independent sensitivity analysis (SA) technique for reducing the model uncertainty has attracted a great deal of attention from analysts and practitioners. It aims at measuring the relative importance of an individual input, or a set of inputs, in determining the uncertainty of model output by looking at the entire distribution range of model output. In this article, along the lines of Plischke et al., we point out that the original moment‐independent SA index (also called delta index) can also be interpreted as the dependence measure between model output and input variables, and introduce another moment‐independent SA index (called extended delta index) based on copula. Then, nonparametric methods for estimating the delta and extended delta indices are proposed. Both methods need only a set of samples to compute all the indices; thus, they conquer the problem of the “curse of dimensionality.” At last, an analytical test example, a risk assessment model, and the levelE model are employed for comparing the delta and the extended delta indices and testing the two calculation methods. Results show that the delta and the extended delta indices produce the same importance ranking in these three test examples. It is also shown that these two proposed calculation methods dramatically reduce the computational burden.     

Improving the detection of unusual observations in high‐dimensional settings

Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T² statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits. However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the monitoring procedure in high‐dimensional settings. We regularise the covariance matrix to estimate the baseline parameter and incorporate a leave‐one‐out re‐sampling approach to estimate the empirical distribution of future observations. An extensive simulation study demonstrates that the new method outperforms the classical Hotelling T² approach in power, and maintains appropriate false positive rates. We demonstrate the utility of the method using a set of quality control samples collected to monitor a gas chromatography–mass spectrometry apparatus over a period of 67 days.     

Improving Risk Management: From Lame Excuses to Principled Practice

The three classic pillars of risk analysis are risk assessment (how big is the risk and how sure can we be?), risk management (what shall we do about it?), and risk communication (what shall we say about it, to whom, when, and how?). We propose two complements as important parts of these three bases: risk attribution (who or what addressable conditions actually caused an accident or loss?) and learning from experience about risk reduction (what works, and how well?). Failures in complex systems usually evoke blame, often with insufficient attention to root causes of failure, including some aspects of the situation, design decisions, or social norms and culture. Focusing on blame, however, can inhibit effective learning, instead eliciting excuses to deflect attention and perceived culpability. Productive understanding of what went wrong, and how to do better, thus requires moving past recrimination and excuses. This article identifies common blame‐shifting “lame excuses” for poor risk management. These generally contribute little to effective improvements and may leave real risks and preventable causes unaddressed. We propose principles from risk and decision sciences and organizational design to improve results. These start with organizational leadership. More specifically, they include: deliberate testing and learning—especially from near‐misses and accident precursors; careful causal analysis of accidents; risk quantification; candid expression of uncertainties about costs and benefits of risk‐reduction options; optimization of tradeoffs between gathering additional information and immediate action; promotion of safety culture; and mindful allocation of people, responsibilities, and resources to reduce risks. We propose that these principles provide sound foundations for improving successful risk management.     

Convergence rate of wavelet density estimator with data missing randomly when covariables are present

In this article, we study global L₂ error of non linear wavelet estimator of density in the Besov space B^s_pq for missing data model when covariables are present and prove that the estimator can achieve the optimal rate of convergence, which is similar to the result studied by Donoho et al. (1996) Donoho, D.L., Johnstone, I.M., Kerkyacharian, G., Picard, D. (1996). Density estimation by wavelet thresholding. Ann. Stat. 24:508–539.[Crossref], [Web of Science ®] , [Google Scholar] in complete independent data case with term-by-term thresholding of the empirical wavelet coefficients. Finite-sample behavior of the proposed estimator is explored via simulations.     

Differential predictors of academic achievement: individual and familial factor interactions with community poverty

We present an analysis of the contexts within which adolescents graduate from high school and enroll in college. Data from the National Longitudinal Study of Adolescent Health show that adolescents’ school engagement, maternal academic monitoring, and community poverty significantly interact to explain differences in high school graduation and college enrollment rates (n?=?7100). To examine this association, we performed weighted logistic regression analyses, controlling for gender, race, block level unemployment, and block level median income. Findings suggest that protective factors can help youth overcome the challenges associated with community poverty and achieve academically in low and medium levels of poverty, but that youth in high-poverty contexts may need more resources to reach higher levels of academic attainment.     

深圳市海外高层次人才引进对三亚市的借鉴与启示

当今人才作为第一资源是各国家与地区之间争夺的对象，如何引进、使用和留住人才对国家和地区的经济发展具有重要意义。深圳市是全国改革开放的先锋军，在海外高层次人才引进方面走在全国前列。对深圳市海外高层次人才引进特色和优势分析，可为三亚市海外高层次人才的引进提供借鉴和启示意义，以促进三亚市发挥自身优势，吸引优势人才资源，为建设海南省国际旅游岛做出一份贡献。     

The influence function of the optimal bandwidth for kernel density estimation

Theories about the bandwidth of kernel density estimation have been well established by many statisticians. However, the influence function of the bandwidth has not been well investigated. The influence function of the optimal bandwidth that minimizes the mean integrated square error is derived and the asymptotic property of the bandwidth selectors based on the influence function is provided.     

Asymptotic approximations to the distribution of Kendall's sample τ

This paper provides a saddlepoint approximation to the distribution of the sample version of Kendall's τ, which is a measure of association between two samples. The saddlepoint approximation is compared with the Edgeworth and the normal approximations, and with the bootstrap resampling distribution. A numerical study shows that with small sample sizes the saddlepoint approximation outperforms both the normal and the Edgeworth approximations. This paper gives also an analytical comparison between approximated and exact cumulants of the sample Kendall's τ when the two samples are independent.     

Same-Sex Sexuality and Educational Attainment: The Pathway to College

Research finds lower levels of academic performance among sexual minority high school students, but some studies suggest sexual minorities have higher levels of educational attainment in adulthood. To further our understanding of how and why sexual orientation is associated with educational success, this study turns attention to the pathways to college completion, examining points along educational trajectories in which sexual minorities fall behind or surpass their heterosexual peers. Using data from the National Longitudinal Study of Adolescent to Adult Health, we find that sexual minority women are less likely than women with no same-sex sexuality to complete college, in part due to their high school performance and transition into college. Men who experience same-sex sexuality only in adolescence struggle in high school, but men who experience same-sex sexuality for the first time in adulthood are more likely to earn a college degree than men who do not experience same-sex sexuality.     

论科学证据的两种概率解释

在科学证据研究中,存在＂正相关＂和＂高概率＂两种科学证据的概率定义。从这两个定义出发,能够比较清晰直观地解释科学证据的许多相关问题,如科学证据中的＂比较级＂和＂可接受性＂等。然而,两个定义自身存在着不可忽视的缺陷：＂正相关＂不是证据的充要条件,＂高概率＂也不足以使证据之为证据。