Approximation algorithms for connected facility location problems

We study Connected Facility Location problems. We are given a connected graph G=(V,E) with nonnegative edge cost c _e for each edge e∈E, a set of clients D⊆V such that each client j∈D has positive demand d _j and a set of facilities F⊆V each has nonnegative opening cost f _i and capacity to serve all client demands. The objective is to open a subset of facilities, say , to assign each client j∈D to exactly one open facility i(j) and to connect all open facilities by a Steiner tree T such that the cost is minimized for a given input parameter M≥1. We propose a LP-rounding based 8.29 approximation algorithm which improves the previous bound 8.55 (Swamy and Kumar in Algorithmica, 40:245–269, 2004). We also consider the problem when opening cost of all facilities are equal. In this case we give a 7.0 approximation algorithm.     

Universal domination of stein-type estimators

For the problem of estimating the location parameter of a p-variate spherically symmetric distribution (p>3), Hwang (1985) established the dominance of some positive-part James-Stein (1961) estimators over the usual estimator simultaneously under a very general class of loss function. Vie show that many of his results can be extended to a class of positive-part Baranchik-type estimators (1970).     

Simplified Maximum Likelihood Inference Based on the Likelihood Decomposition for Missing Data

In this paper, we propose an estimation method when sample data are incomplete. We decompose the likelihood according to missing patterns and combine the estimators based on each likelihood weighting by the Fisher information ratio. This approach provides a simple way of estimating parameters, especially for non‐monotone missing data. Numerical examples are presented to illustrate this method.     

Directional Dependence of Genes Using Survival Truncated FGM Type Modification Copulas

Ordinal data, such as student's grades or customer satisfaction surveys, are widely used in daily life. We can fit a probit or logistic regression model to the ordinal data using software such as SAS and get the estimates of regression parameters. However, it is hard to define residuals and detect outliers due to the fact that the estimated probabilities of an observation falling in every category form a vector instead of a scalar. With the help of latent variable and latent residuals, a Bayesian perspective of detecting outliers is explored and several methods were proposed in this article. Several figures are also given.     

Bayesian False Discovery Rate Wavelet Shrinkage: Theory and Applications

Statistical inference in the wavelet domain remains a vibrant area of contemporary statistical research because of desirable properties of wavelet representations and the need of scientific community to process, explore, and summarize massive data sets. Prime examples are biomedical, geophysical, and internet related data. We propose two new approaches to wavelet shrinkage/thresholding.

In the spirit of Efron and Tibshirani's recent work on local false discovery rate, we propose Bayesian Local False Discovery Rate (BLFDR), where the underlying model on wavelet coefficients does not assume known variances. This approach to wavelet shrinkage is shown to be connected with shrinkage based on Bayes factors. The second proposal, Bayesian False Discovery Rate (BaFDR), is based on ordering of posterior probabilities of hypotheses on true wavelets coefficients being null, in Bayesian testing of multiple hypotheses.

We demonstrate that both approaches result in competitive shrinkage methods by contrasting them to some popular shrinkage techniques.     

A Regression Model for the AUC of Clustered Ordinal Test Results and Working Independent Optimal Weights

We study a regression model on the area under the receiver operating characteristic curves (AUC) for clustered (or repeatedly measured) test results. To account for cluster information, we consider a weighted estimating equation for Dodd and Pepe (2003 Dodd , L. , Pepe , M. ( 2003 ). Semiparametric regression for the area under the receiver operating charateristic curve . Journal of the American Statistical Association 98 : 409 – 417 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar])'s regression model with working independence weights. We find the optimal weight in the given class of working independence weights to minimize the variance (or MSE) of regression estimators. We apply the proposed procedure to analyzing our recent experiment on diagnosing a liver disorder. In this experiment, we investigated MRI images of patients having symptoms of potential liver disorder to compare the performance of different MRI picturing methods in testing for liver disorders.     

Homelessness and Children's Use of Mental Health Services: A Population-Based Study

This study examined whether children who become homeless differ from other low-income children in their mental health service use before and after their first homeless episode, and to what extent homelessness is associated with an increased likelihood of mental health service use. Differences between children with and without new onset of sheltered homelessness in the use of mental health services emerged following homelessness and widened over time. Sheltered homelessness and foster care placement history were associated with increased odds of receiving inpatient and ambulatory mental health services. Findings underscore the importance of collaborations between homeless assistance, foster care, and mental healthcare in efforts to mitigate family homelessness and collateral needs among homeless children.     

Bending but Not Breaking?: Foreign Investor Pressure and Dividend Payouts by Japanese Firms

This article examines the global diffusion of shareholder‐oriented governance practices, using the case of dividend payouts by Japanese firms. While Japanese firms previously retained profits for rainy days or new ventures, their dividend payouts began to increase in the 1990s, rapidly catching up with the levels prevailing in the United States. Following prior research, we focus on the role of foreign investors in this process but provide a more nuanced account of their influence, using panel data on 2,036 publicly traded Japanese firms from 1990 to 2005. First, we show that pressure from foreign investors increased dividends by Japanese firms not only directly but also indirectly, by extending the cognitive boundaries of organizational fields of Japanese firms beyond their local peers and toward their global competitors. Second, we show that although Japanese firms that remained deeply embedded in the traditional, stakeholder‐oriented governance system resisted shareholder‐oriented governance practices, even such firms yielded under pressure from both foreign and domestic investors. We conclude with theoretical implications of our findings for the literature on the global diffusion of shareholder value and its broader political and social consequences.     

A Moderated Mediation Model of Planned Happenstance Skills,Career Engagement,Career Decision Self‐Efficacy,and Career Decision Certainty

This study examined how college students’ levels of planned happenstance skills influenced the relationships among career engagement, career decision self‐efficacy, and career decision certainty. Moderated mediation analysis was used with a sample of 217 Korean undergraduate students. The results indicated that career decision self‐efficacy mediated the relationship between career engagement and career decision certainty. Moreover, the positive indirect effect of career engagement on career decision through career decision self‐efficacy was strengthened as the level of planned happenstance skills increased. In conclusion, college students’ career engagement strengthens their career decision certainty via career decision self‐efficacy when they have enough planned happenstance skills to discover unexpected career opportunities.     

Construction and Initial Validation of the Planned Happenstance Career Inventory

This study was conducted to develop and initially evaluate the psychometric properties of the Planned Happenstance Career Inventory (PHCI), which aims to assess skill in using chance events to develop career opportunities. After item generation and exploratory factor analysis, 130 original items were reduced to 25 items across 5 factors (5 items for each corresponding factor). Multigroup confirmatory factor analysis confirmed the validity of this 5‐factor structure, and the goodness of fit showed an adequate fit to the observed data for both women and men. Results showed that PHCI subscales correlated moderately and in expected directions with career preparation, career decision‐making self‐efficacy, and career stress. These findings suggest that the PHCI, which assesses 5 dimensions of career‐related planned happenstance skill, shows promise as a useful tool for facilitating understanding of the influence of chance events on career choice behavior.