introduction: the important of comparing performance of hospitals using hospital indicators, has been made the necessary of utilizing of the application model inevitable. this study aimed to compare hospital performance key indicators simultaneity. methods: in this descriptive cross sectional and retrospective study, 31 hospitals of isfahan university of medical sciences were evaluated in 2007....

We consider the graphical lasso formulation for estimating a Gaussian graphical model in the high-dimensional setting. This approach entails estimating the inverse covariance matrix under a multivariate normal model by maximizing the 1-penalized log-likelihood. We present a very simple necessary and sufficient condition that can be used to identify the connected components in the graphical lass...

for K linear regressions. The support union of K p-dimensional regression vectors (collected as columns of matrix B∗) is recovered using l1/l2-regularized Lasso. Sufficient and necessary conditions on sample complexity are characterized as a sharp threshold to guarantee successful recovery of the support union. This model has been previously studied via l1/l∞regularized Lasso by Negahban & Wain...

While considerable advances have been made in estimating high-dimensional structured models from independent data using Lasso-type models, limited progress has been made for settings when the samples are dependent. We consider estimating structured VAR (vector auto-regressive model), where the structure can be captured by any suitable norm, e.g., Lasso, group Lasso, order weighted Lasso, etc. I...

Despite the widespread use of liver transplantation as a routine therapy in liver diseases, the effective factors on its outcomes are still controversial. This study attempted to identify the most effective factors on death after liver transplantation. For this purpose, modified least absolute shrinkage and selection operator (LASSO), called Adaptive LASSO, was utilized. One of the best advanta...

BACKGROUND Blindness due to diabetic retinopathy (DR) is the major disability in diabetic patients. Although early management has shown to prevent vision loss, diabetic patients have a low rate of routine ophthalmologic examination. Hence, we developed and validated sparse learning models with the aim of identifying the risk of DR in diabetic patients. METHODS Health records from the Korea Na...

This paper tackles the problem of model complexity in the context of additive models. Several methods have been proposed to estimate smoothing parameters, as well as to perform variable selection. Nevertheless, these procedures are inefficient or computationally expensive in high dimension. Also, the lasso technique has been adapted to additive models, however its experimental performance has n...

This paper proposes a new two stage least squares (2SLS) estimator which is consistent and asymptotically normal in the presence of many weak instruments and heteroskedasticity. The first stage of the estimator consists of two components: first, an adaptive absolute shrinkage and selection operator (LASSO) that selects the instruments; and second, an OLS regression with the selected regressors....

Steady-state visual evoked potential (SSVEP) has been increasingly used for the study of brain–computer interface (BCI). How to recognize SSVEP with shorter time and lower error rate is one of the key points to develop a more efficient SSVEP-based BCI. To achieve this goal, we make use of the sparsity constraint of the least absolute shrinkage and selection operator (LASSO) for the extraction o...