Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.     

试析卞之琳早期诗歌创作之风格

精湛的艺术技巧和深刻的思想深度的高度统一,是卞之琳对中国现代诗歌的杰出贡献,也是他被称为中国现代杰出诗人的一个重要原因。纵观卞之琳30年代的诗歌创作,不难发现,对人生的沉思,是其诗歌持久的主题。这种沉思是以两种形式表现的:一是对自我以外的人生形式和生活态度的沉思,一是直接对自我人生的体验和沉思。就思想性而言,卞之琳30年代诗歌的重要特征就在于:它是诗人对人生的体验和沉思的结晶。     

Multivariate Control Charts Based on Hybrid Novelty Scores

We propose a new nonparametric multivariate control chart that integrates a novelty score. The proposed control chart uses as its monitoring statistic a hybrid novelty score, calculated based on the distance to local observations as well as on the distance to the convex hull constructed by its neighbors. The control limits of the proposed control chart were established based on a bootstrap method. A rigorous simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compare it with existing multivariate control charts in terms of average run length (ARL) performance. The simulation results showed that the proposed control chart outperformed both the parametric and nonparametric Hotelling's T ² control charts, especially in nonnormal situations. Moreover, experimental results with real semiconductor data demonstrated the applicability and effectiveness of the proposed control chart. To increase the capability to detect small mean shift, we propose an exponentially weighted hybrid novelty score control chart. Simulation results indicated that exponentially weighted hybrid score charts outperformed the hybrid novelty score based control charts.     

Analysis of Local Acceptance of a Radioactive Waste Disposal Facility

Like many other countries in the world, Korea has struggled to site a facility for radioactive waste for almost 30 years because of the strong opposition from local residents. Finally, in 2005, Gyeongju was established as the first Korean site for a radioactive waste facility. The objectives of this research are to verify Gyeongju citizens' average level of risk perception of a radioactive waste disposal facility as compared to other risks, and to explore the best model for predicting respondents' acceptance level using variables related to cost-benefit, risk perception, and political process. For this purpose, a survey is conducted among Gyeongju residents, the results of which are as follows. First, the local residents' risk perception of an accident in a radioactive waste disposal facility is ranked seventh among a total of 13 risks, which implies that nuclear-related risk is not perceived very highly by Gyeongju residents; however, its characteristics are still somewhat negative. Second, the comparative regression analyses show that the cost-benefit and political process models are more suitable for explaining the respondents' level of acceptance than the risk perception model. This may be the result of the current economic depression in Gyeongju, residents' familiarity with the nuclear industry, or cultural characteristics of risk tolerance.     

A pragmatic algorithm for the train-set routing: The case of Korea high-speed railway

This paper presents a two-phased train-set routing algorithm to cover a weekly train timetable with minimal working days of a minimal number of train-sets. First, relax maintenance requirements and obtain minimum cost routes by solving the polynomial relaxation. Then, maintenance-feasible routes are generated from the crossovers of the minimum cost routes. This pragmatic approach seems particularly effective for the high-speed railway systems, where the railway topology is relatively simple with few end stations while the trains are frequent. Applied to the current weekly timetable of the Korea high-speed railway, we could find an optimal feasible routing, which is an 8.8% improvement over the current routing generated by a set partitioning approach based on a path generation scheme.     

One-Class Classification-Based Control Charts for Monitoring Autocorrelated Multivariate Processes

In recent years, statistical process control (SPC) of multivariate and autocorrelated processes has received a great deal of attention. Modern manufacturing/service systems with more advanced technology and higher production rates can generate complex processes in which consecutive observations are dependent and each variable is correlated. These processes obviously violate the assumption of the independence of each observation that underlies traditional SPC and thus deteriorate the performance of its traditional tools. The popular way to address this issue is to monitor the residuals—the difference between the actual value and the fitted value—with the traditional SPC approach. However, this residuals-based approach requires two steps: (1) finding the residuals; and (2) monitoring the process. Also, an accurate prediction model is necessary to obtain the uncorrelated residuals. Furthermore, these residuals are not the original values of the observations and consequently may have lost some useful information about the targeted process. The main purpose of this article is to examine the feasibility of using one-class classification-based control charts to handle multivariate and autocorrelated processes. The article uses simulated data to present an analysis and comparison of one-class classification-based control charts and the traditional Hotelling's T ² chart.     

Asymptotic Properties of the Empirical Spatial Extremogram

The extremogram is a useful tool for measuring extremal dependence and checking model adequacy in a time series. We define the extremogram in the spatial domain when the data is observed on a lattice or at locations distributed as a Poisson point process in d‐dimensional space. We establish a central limit theorem for the empirical spatial extremogram. We show these conditions are applicable for max‐moving average processes and Brown–Resnick processes and illustrate the empirical extremogram's performance via simulation. We also demonstrate its practical use with a data set related to rainfall in a region in Florida and ground‐level ozone in the eastern United States.     

Differences in the relationship between depression and self-rated life satisfaction in older Korean and Chinese immigrants

This study aims to examine self-rated life satisfaction and describe its relationship with depression and socioeconomic status among older Chinese and Korean immigrants. A cross-sectional study of 175 older Chinese immigrants and 205 older Korean immigrants was conducted in Los Angeles County. The study found that depression was negatively associated with self-rated life satisfaction for both the Chinese and Korean groups. For older Chinese immigrants, depression was the only significant factor related to self-rated life satisfaction. However, for older Korean immigrants, age, education, and depression were significantly associated with self-rated life satisfaction. This study suggests empirical strategies to reduce depression among these populations, such as the importance of culturally-tailored programs.