abstract background: pabon lasso model was applied to assess the relative performance of hospitals affiliated to kurdistan university of medical sciences (kums) before and after the implementation of health sector evolution plan (hsep) in iran. methods: this cross-sectional study was carried out in 11 public hospitals affiliated to kums in 2015. twelve months before and after the implementation...

2 3 Preface Many classification procedures are based on variable selection methodologies. This master thesis concentrates on continuous variable selection procedures based on the shrinkage principle. Generally, we would like to find sparse prediction rules for multi-class classification problems such that in increases the prediction accuracy but also the interpretability of the obtained predict...

The lasso peptide microcin J25 is known to hijack the siderophore receptor FhuA for initiating internalization. Here, we provide what is to our knowledge the first structural evidence on the recognition mechanism, and our biochemical data show that another closely related lasso peptide cannot interact with FhuA. Our work provides an explanation on the narrow activity spectrum of lasso peptides ...

background and objectives: the large contribution of hospitals to the function and expenditures of the healthsector makes their constant monitoring and evaluation inevitable to improve the overall performance of the health system. built on that, the present study aimed to evaluate the trend of performance of hospitals affiliated with the public hospitals (in guilan province, iran) affiliated wi...

In this paper, we investigate the degrees of freedom (dof) of penalized `1 minimization (also known as the Lasso) for linear regression models. We give a closed-form expression of the dof of the Lasso response. Namely, we show that for any given Lasso regularization parameter λ and any observed data y belonging to a set of full (Lebesgue) measure, the cardinality of the support of a particular ...

Multiple imputation (MI) is a commonly used technique for handling missing data in large-scale medical and public health studies. However, variable selection on multiply-imputed data remains an important and longstanding statistical problem. If a variable selection method is applied to each imputed dataset separately, it may select different variables for different imputed datasets, which makes...

We propose the use of the Least Absolute Shrinkage and Selection Operator (LASSO) regression method in order to predict the Cumulative Mean Squared Error (CMSE), incurred by the loss of individual slices in video transmission. We extract a number of quality-relevant features from the H.264/AVC video sequences, which are given as input to the LASSO. This method has the benefit of not only keepin...

The Lasso has been widely studied and used in many applications over the last decade. It has also been extended in various directions in particular to ensure asymptotic oracle properties through adaptive weights (Zou, 2006). Another direction has been to incorporate additional knowledge within the penalty to account for some structure among features. Among such strategies the Fused-Lasso (Tibsh...

Stochastic chemical reaction networks constitute a model class to quantitatively describe dynamics and cell-to-cell variability in biological systems. The topology of these networks typically is only partially characterized due to experimental limitations. Current approaches for refining network topology are based on the explicit enumeration of alternative topologies and are therefore restricte...