In the high-dimensional regression model a response variable is linearly related to p covariates, but the sample size n is smaller than p. We assume that only a small subset of covariates is ‘active’ (i.e., the corresponding coefficients are non-zero), and consider the model-selection problem of identifying the active covariates. A popular approach is to estimate the regression coefficients thr...

Lasso is a popular method for variable selection in regression. Much theoretical understanding has been obtained recently on its model selection or sparsity recovery properties under sparse and homoscedastic linear regression models. Since these standard model assumptions are often not met in practice, it is important to understand how Lasso behaves under nonstandard model assumptions. In this ...

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 ...