Hard thresholding regression

In this paper, we propose the hard thresholding regression (HTR) for estimating high‐dimensional sparse linear regression models. HTR uses a two‐stage convex algorithm to approximate the ?₀‐penalized regression: The first stage calculates a coarse initial estimator, and the second stage identifies the oracle estimator by borrowing information from the first one. Theoretically, the HTR estimator achieves the strong oracle property over a wide range of regularization parameters. Numerical examples and a real data example lend further support to our proposed methodology.     

Quadratic Approximation via the SCAD Penalty with a Diverging Number of Parameters

The high-dimensional data arises in diverse fields of sciences, engineering and humanities. Variable selection plays an important role in dealing with high dimensional statistical modelling. In this article, we study the variable selection of quadratic approximation via the smoothly clipped absolute deviation (SCAD) penalty with a diverging number of parameters. We provide a unified method to select variables and estimate parameters for various of high dimensional models. Under appropriate conditions and with a proper regularization parameter, we show that the estimator has consistency and sparsity, and the estimators of nonzero coefficients enjoy the asymptotic normality as they would have if the zero coefficients were known in advance. In addition, under some mild conditions, we can obtain the global solution of the penalized objective function with the SCAD penalty. Numerical studies and a real data analysis are carried out to confirm the performance of the proposed method.     

耶律阿保机对世选制的调整与利用

阿保机时代是契丹社会大变革的时代,阿保机变革旧制的一个内容就是对传统世选制的改造。经过他的努力,从理论意义上实现了契丹可汗世选向皇位世袭的转变,也对官吏的世选作了重大的调整。值得重视的是,阿保机的政治智慧在变革世选制过程中有所体现。     

A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem

In this paper, multiple criteria sorting methods based on data envelopment analysis (DEA) are developed to evaluate research and development (R&D) projects. The weight intervals of the criteria are obtained from Interval Analytic Hierarchy Process and employed as the assurance region constraints of models. Based on data envelopment analysis, two threshold estimation models, and five assignment models are developed for sorting. In addition to sorting, these models also provide ranking of the projects. The developed approach and the well-known sorting method UTADIS are applied to a real case study to analyze the R&D projects proposed to a grant program executed by a government funding agency in 2009. A five level R&D project selection criteria hierarchy and an assisting point allocation guide are defined to measure and quantify the performance of the projects. In the case study, the developed methods are observed to be more stable than UTADIS.     

Robust modal estimation and variable selection for single-index varying-coefficient models

In this article, we present a new efficient iteration estimation approach based on local modal regression for single-index varying-coefficient models. The resulted estimators are shown to be robust with regardless of outliers and error distributions. The asymptotic properties of the estimators are established under some regularity conditions and a practical modified EM algorithm is proposed for the new method. Moreover, to achieve sparse estimator when there exists irrelevant variables in the index parameters, a variable selection procedure based on SCAD penalty is developed to select significant parametric covariates and the well-known oracle properties are also derived. Finally, some numerical examples with various distributed errors and a real data analysis are conducted to illustrate the validity and feasibility of our proposed method.     

Partner Violence in Transgender Communities: What Helping Professionals Need to Know

ABSTRACT

In recent decades, there has been an increase in scholarly attention devoted to the study of intimate partner violence (IPV) within rainbow communities. While a growing body of scholarship now informs our understanding of the experiences of gay, lesbian, and bisexual men and women with IPV, comparatively less is known about IPV within transgender communities. Drawing on the published literature on transgender intimate relationships, this article seeks to provide practitioners with a foundational understanding of IPV in the lives of transgender people. Specifically, we will examine (a) methodological, political, and social barriers to the creation of knowledge about transgender IPV; (b) the familial and relationship contexts of IPV within transgender communities; (c) the prevalence of IPV experienced by transgender survivors; (d) the dynamics of IPV perpetrated against and/or by transgender persons; (e) the problematic use of the “trans panic” defense by perpetrators of IPV in legal contexts; and (f) recommendations for supporting transgender survivors of IPV in ways that are trans-inclusive and trans-positive.     

A Method to Handle Zero Counts in the Multinomial Model

In the context of an objective Bayesian approach to the multinomial model, Dirichlet(a, …, a) priors with a < 1 have previously been shown to be inadequate in the presence of zero counts, suggesting that the uniform prior (a = 1) is the preferred candidate. In the presence of many zero counts, however, this prior may not be satisfactory either. A model selection approach is proposed, allowing for the possibility of zero parameters corresponding to zero count categories. This approach results in a posterior mixture of Dirichlet distributions and marginal mixtures of beta distributions, which seem to avoid the problems that potentially result from the various proposed Dirichlet priors, in particular in the context of extreme data with zero counts.     

“I'm Not Supporting His Kids”: Nonresident Fathers' Contributions Given Mothers' New Fertility

The authors examined whether nonresident fathers provide informal support to their children and whether support stops if their ex‐partner goes on to have a child with a new man. A logistic regression analysis of longitudinal survey and administrative data for 434 women who received welfare in Wisconsin showed that fathers are less likely to provide informal support when their ex‐partner has a child with a new partner. Alternative models that control for unobserved characteristics suggest somewhat different results, providing stronger evidence of declines in support that can be shared across family members than in support that can be directed to a particular child.