A new distribution-free k-sample test: Analysis of kernel density functionals

A novel distribution-free k-sample test of differences in location shifts based on the analysis of kernel density functional estimation is introduced and studied. The proposed test parallels one-way analysis of variance and the Kruskal–Wallis (KW) test aiming at testing locations of unknown distributions. In contrast to the rank (score)-transformed non-parametric approach, such as the KW test, the proposed F-test uses the measurement responses along with well-known kernel density estimation (KDE) to estimate the locations and construct the test statistic. A practical optimal bandwidth selection procedure is also provided. Our simulation studies and real data example indicate that the proposed analysis of kernel density functional estimate (ANDFE) test is superior to existing competitors for fat-tailed or heavy-tailed distributions when the k groups differ mainly in location rather than shape, especially with unbalanced data. ANDFE is also highly recommended when it is unclear whether test groups differ mainly in shape or location. The Canadian Journal of Statistics 48: 167–186; 2020 © 2019 Statistical Society of Canada     

Bayesian prediction of unobserved values for Type-II censored data

In this paper, we consider posterior predictive distributions of Type-II censored data for an inverse Weibull distribution. These functions are given by using conditional density functions and conditional survival functions. Although the conditional survival functions were expressed by integral forms in previous studies, we derive the conditional survival functions in closed forms and thereby reduce the computation cost. In addition, we calculate the predictive confidence intervals of unobserved values and coverage probabilities of unobserved values by using the posterior predictive survival functions.     

Risk of Large‐Scale Evacuation Based on the Effectiveness of Rescue Strategies Under Different Crowd Densities

Crowd density is a key factor that influences the moving characteristics of a large group of people during a large‐scale evacuation. In this article, the macro features of crowd flow and subsequent rescue strategies were considered, and a series of characteristic crowd densities that affect large‐scale people movement, as well as the maximum bearing density when the crowd is extremely congested, were analyzed. On the basis of characteristic crowd densities, the queuing theory was applied to simulate crowd movement. Accordingly, the moving characteristics of the crowd and the effects of typical crowd density—which is viewed as the representation of the crowd's arrival intensity in front of the evacuation passageways—on rescue strategies was studied. Furthermore, a “risk axle of crowd density” is proposed to determine the efficiency of rescue strategies in a large‐scale evacuation, i.e., whether the rescue strategies are able to effectively maintain or improve evacuation efficiency. Finally, through some rational hypotheses for the value of evacuation risk, a three‐dimensional distribution of the evacuation risk is established to illustrate the risk axle of crowd density. This work aims to make some macro, but original, analysis on the risk of large‐scale crowd evacuation from the perspective of the efficiency of rescue strategies.     

Nonparametric estimation of the entropy using a ranked set sample

This article is concerned with nonparametric estimation of the entropy in ranked set sampling. Theoretical properties of the proposed estimator are studied. The proposed estimator is compared with the rival estimator in simple random sampling. The applications of the proposed estimator to the mutual information estimation as well as estimation of the Kullback–Leibler divergence are provided. Several Monté-Carlo simulation studies are conducted to examine the performance of the estimator. The results are applied to the longleaf pine (Pinus palustris) trees and the body fat percentage datasets to illustrate applicability of theoretical results.     

Comment on testing for spurious and cointegrated regressions: a wavelet approach

In a recent paper, Leong and Huang [6] proposed a wavelet-correlation-based approach to test for cointegration between two time series. However, correlation and cointegration are two different concepts even when wavelet analysis is used. It is known that statistics based on non-stationary integrated variables have non-standard asymptotic distributions. However, wavelet analysis offsets the integrating order of non-stationary series so that traditional asymptotics on stationary variables suffices to ascertain the statistical properties of wavelet-based statistics. Based on this, this note shows that wavelet correlations cannot be used as a test of cointegration.     

中外耐力性项目训练负荷强度安排特征比较研究

通过中外教练员对耐力项目运动员负荷强度安排特征比较,并结合我国优秀女子马拉松运动员训练实践数据分析发现：优秀耐力运动员更倾向于采用大量低强度负荷构建牢固的耐力基础,在此基础上适当安排90%左右的负荷强度,即两极化训练,是最佳的训练模式.这也为改变中国教练员片面将优秀女子马拉松运动员比赛中后半程速度下降原因归于＂大强度＂训练不足的盲目现象提供了依据.     

楔形域上Modified-Helmholtz方程的混合边值问题

考虑一类楔形域上Modified-Helmholtz方程的混合边值问题.利用新型的Fokas谱变换方法,将问题转化为求解一类Riemann-Hilbert边值问题,从而得到了方程解的封闭积分表达式.     

抓好速度耐力,突出强度,提高密度——高校中长跑训练方式之谈

高校进行中长跑训练是高校办高水平运动队的产物,运动员以在校大学生为主,运动员一边学习一边训练,属于"边学边训性",运动训练具有较强的业余性。这一特点决定了高校运动队不能采用专业队的训练方法和标准,而应立足于自身的现实条件,去寻找适合自己的训练方法。高校中长跑项目的教学、训练应结合高校体育教育的特点,抓好速度耐力,突出专项,突出强度,提高密度,对运动员运动成绩的提高效果比较理想。     

论公用设施和人口密度对小城镇经济增长贡献

利用2005和2010年数据,在评价各地区小城镇公用设施存量水平基础上,利用引入人口密度变量扩展的巴罗模型测算公用设施对小城镇财政收入的贡献。实证发现,各类公用设施、人口密度和镇区面积变量对小城镇经济增长的贡献显著。有侧重地优先保障中西部地区民生类基础设施的供给,扩大小城镇镇区规模和提高人口密度,以及采取有进有退小城镇发展战略,对于促进经济增长非常重要。     

Screening Elders in the Emergency Department at Risk for Mistreatment: A Pilot Study

Impaired functional status is associated with risk of elder mistreatment. Screening for functional impairment in elderly patients admitted to emergency departments could be performed to identify patients at risk for elder mistreatment who might benefit from further evaluation. This study utilized a modified Identification of Seniors at Risk (ISAR) screening tool to identify the proportion of elderly at risk for mistreatment due to functional difficulties presenting to two emergency departments in southeastern Virginia, one urban, the other rural. Of a 180-patient cohort (90 per site), 82 screened positive (46%), ISAR > 2 (range 0–6), indicating nearly half of all patients enrolled are at risk for mistreatment. Patients presenting to the urban emergency departments were potentially more at risk than their rural counterparts (p < 0.01). Health care professionals, particularly in urban settings, should consider screening seniors with a simple tool to identify patients at risk of elder mistreatment.