seagull: lasso, group lasso and sparse-group lasso regularisation for linear regression models via proximal gradient descent

Published: Feb 14, 2020
Abstract
Statistical analyses of biological problems in life sciences often lead to high-dimensional linear models. To solve the corresponding system of equations, penalisation approaches are often the methods of choice. They are especially useful in case of multicollinearity which appears if the number of explanatory variables exceeds the number of ob-servations or for some biological reason. Then, the model goodness of fit is penalised by some suitable...
Paper Details
Title
seagull: lasso, group lasso and sparse-group lasso regularisation for linear regression models via proximal gradient descent
Published Date
Feb 14, 2020
Journal
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