SpaSM: A MATLAB Toolbox for Sparse Statistical Modeling

• DOI: 10.18637/jss.v084.i10
• Publication Date: 2018-04-23T17:24:36Z
• Authors: Karl Sjöstrand; Line Harder Clemm...; Rasmus Larsen; Gudmundur Einarsson; Bjarne Ersbøll
• Keywords: Implementation; Toolbox; Underdetermined system; Code (set theory)

Applications in biotechnology such as gene expression analysis and image processing have led to a tremendous development of statistical methods with emphasis on reliable solutions severely underdetermined systems. Furthermore, interpretations are importance, meaning that the surplus inputs has been reduced concise model. At core this which augment standard linear models for regression, classification decomposition sparse obtained. This toolbox aims at making public available carefully implemented well-tested variants most popular MATLAB programming environment. These consist easy-to-read yet efficient implementations various coefficient-path following algorithms principal component discriminant not MATLAB. The builds code made 2005 since used several studies.