Jack’d,a Mobile Social Networking Application: A Site of Exclusion Within a Site of Inclusion

User-generated smartphone applications have created a new level of virtual connectivity for gay males, one in which users can create profiles and meet other users as nearby or as far away as possible. For those within close proximity, the other users can be considered their “virtual neighbors.” Although the applications are theoretically designed to be places of inclusion and not exclusion, where any gay male with economic means can download an application, many profiles have been created that exclude other users. Through an examination of profiles on one such application, Jack’d, exclusion is found in the way users celebrate and reinforce ideas of traditional masculinity and denigrate and reinforce stereotypic ideas of femininity embodied by some gay men. Jack’d, and other user-generated smartphone applications, can be read as virtual neighborhoods where one is excluded based on their gender performance.     

习近平贫困治理重要论述的理论意蕴及在四川藏区的实践应用

习近平关于贫困治理的系列重要论述承载着丰富的理论意蕴：其一,改革创新是贫困治理的长效保障;其二,人民群众是贫困治理的基石和源泉;其三,精准扶贫是全面建成小康社会的必要路径。本文立足于习近平贫困治理重要论述的理论意蕴,构建了精准扶贫与精细化治理有效对接的理论分析框架,对四川藏区贫困治理的现状及问题进行了深入分析,指出在后精准脱贫阶段,进一步增强四川藏区扶贫实效,需要创新集聚启动机制、完善瞄准定位机制、构建利益联结机制、健全监测调控机制、探索益贫发展机制、构建应急机制。     

Efficiency of the QR class estimator in semiparametric regression models to combat multicollinearity

There are some classes of biased estimators for solving the multicollinearity among the predictor variables in statistical literature. In this research, we propose a modified estimator based on the QR decomposition in the semiparametric regression models, to combat the multicollinearity problem of design matrix which makes the data to be less distorted than the other methods. We derive the properties of the proposed estimator, and then, the necessary and sufficient condition for the superiority of the partially generalized QR-based estimator over partially generalized least-squares estimator is obtained. In the biased estimators, selection of shrinkage parameters plays an important role in data analysing. We use generalized cross-validation criterion for selecting the optimal shrinkage parameter and the bandwidth of the kernel smoother. Finally, the Monté-Carlo simulation studies and a real application related to bridge construction data are conducted to support our theoretical discussion.     

Bayesian Tobit quantile regression using g-prior distribution with ridge parameter

A Bayesian approach is proposed for coefficient estimation in the Tobit quantile regression model. The proposed approach is based on placing a g-prior distribution depends on the quantile level on the regression coefficients. The prior is generalized by introducing a ridge parameter to address important challenges that may arise with censored data, such as multicollinearity and overfitting problems. Then, a stochastic search variable selection approach is proposed for Tobit quantile regression model based on g-prior. An expression for the hyperparameter g is proposed to calibrate the modified g-prior with a ridge parameter to the corresponding g-prior. Some possible extensions of the proposed approach are discussed, including the continuous and binary responses in quantile regression. The methods are illustrated using several simulation studies and a microarray study. The simulation studies and the microarray study indicate that the proposed approach performs well.     

Influence in the Elliptical Modified Ridge Regression

In this article, we present diagnostic methods for the modified ridge regression under elliptical model based on the pseudo-likelihood function. The maximum likelihood estimators of the parameters in the modified ridge elliptical model are given and local influence measures are developed. Finally, illustration of our methodology is given through a numerical example.     

Some ridge regression estimators for the zero-inflated Poisson model

The zero-inflated Poisson regression model is commonly used when analyzing economic data that come in the form of non-negative integers since it accounts for excess zeros and overdispersion of the dependent variable. However, a problem often encountered when analyzing economic data that has not been addressed for this model is multicollinearity. This paper proposes ridge regression (RR) estimators and some methods for estimating the ridge parameter k for a non-negative model. A simulation study has been conducted to compare the performance of the estimators. Both mean squared error and mean absolute error are considered as the performance criteria. The simulation study shows that some estimators are better than the commonly used maximum-likelihood estimator and some other RR estimators. Based on the simulation study and an empirical application, some useful estimators are recommended for practitioners.     

The successive raising estimator and its relation with the ridge estimator

The raised estimators are used to reduce collinearity in linear regression models by raising a column in the experimental data matrix which may be nearly linear with the other columns. The raising procedure has two components, namely stretching and rotating, which we can analyze separately. We give the relationship between the raised estimators and the classical ridge estimators. Using a case study, we show how to determine the perturbation parameter for the raised estimators by controlling the amount of precision to be retained in the original data.     

On the restricted almost unbiased two-parameter estimator in linear regression model

Özkale and Kaçiranlar introduced the restricted two-parameter estimator (RTPE) to deal with the well-known multicollinearity problem in linear regression model. In this paper, the restricted almost unbiased two-parameter estimator (RAUTPE) based on the RTPE is presented. The quadratic bias and mean-squared error of the proposed estimator is discussed and compared with the corresponding competitors in literatures. Furthermore, a numerical example and a Monte Carlo simulation study are given to explain some of the theoretical results.     

国外网络信息的发展与应用

美国具有强大的网络信息优势,在网络信息的发展趋势和应用方面也代表了国外网络信息的发展方向;日本在网络信息的发展和应用方面一直紧跟美国走在世界前列。以美国和日本为代表分析了发达国家信息化发展的社会环境和政策措施,指出了发展中国家如何面对机会和挑战,发展本国的信息化产业。