This study develops a data-driven group variable selection method for data envelopment analysis (DEA), a non-parametric linear programming approach to the estimation of production frontiers. The proposed method extends the group Lasso (least absolute shrinkage and selection operator) designed for variable selection on (often predefined) groups of variables in linear regression models to DEA mod...

Introduction: Single SNP analyses using logistic regression have traditionally been applied in genetic association studies to assess main effects. However, many complex diseases, such as bladder cancer (BC), are likely to be associated with the combined effects of multiple loci. Problems derived from genetic data are that most single SNP analyses are underpowered to detect small effects and so ...

We use a novel penalized approach for genome-wide association study that accounts for the linkage disequilibrium between adjacent markers. This method uses a penalty on the difference of the genetic effect at adjacent single-nucleotide polymorphisms and combines it with the minimax concave penalty, which has been shown to be superior to the least absolute shrinkage and selection operator (LASSO...

Logistic regression analysis may well be used to develop a prognostic model for a dichotomous outcome. Especially when limited data are available, it is difficult to determine an appropriate selection of covariables for inclusion in such models. Also, predictions may be improved by applying some sort of shrinkage in the estimation of regression coefficients. In this study we compare the perform...

Prognostic models based on survival data frequently make use of the Cox proportional hazards model. Developing reliable Cox models with few events relative to the number of predictors can be challenging, even in low-dimensional datasets, with a much larger number of observations than variables. In such a setting we examined the performance of methods used to estimate a Cox model, including (i) ...

To standardize the tea export market and guarantee interest of consumers, adulteration problem in Taiping Houkui should be eliminated. In this study, a screening scheme comprising chemometrics statistical analysis was proposed to estimate geographical origin tea. A total 11 metal ions were detected by performing chemometric experiment. The key variables that can used identify screened using lea...

A general-purpose GPU (GPGPU) is employed in a variety of domains, including accelerating the spread deep natural network models; however, further research into its effective implementation needed. When using compute unified device architecture (CUDA), which has recently gained popularity, situation analogous to use GPUs and memory space. This due lack gold standard for selecting most efficient...

Background: The likelihood of developing Posttraumatic Stress Disorder (PTSD) depends on the interaction of individual risk factors and cumulative traumatic experiences. Hence, the identification of individual susceptibility factors warrants precise quantification of trauma exposure. Previous research indicated that some traumatic events may have more severe influences on mental health than oth...

We investigate the variable selection problem for Cox’s proportional hazards model, and propose a unified model selection and estimation procedure with desired theoretical properties and computational convenience. The new method is based on a penalized log partial likelihood with the adaptively-weighted L1 penalty on regression coefficients, and is named adaptive-LASSO (ALASSO) estimator. Inste...