Matlab implementation of LASSO, LARS, the elastic net and SPCA

Karl Sjöstrand (Author)

    Research output: Non-textual formComputer programmeResearchpeer-review

    275 Downloads (Pure)

    Abstract

    There are a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (LARS) and elastic net (LARS-EN) regression. There also exists a method for calculating principal components with sparse loadings. This software package contains Matlab implementations of these functions. The standard implementations of these functions are available as add-on packages in S-Plus and R.
    Original languageEnglish
    Publication date2005
    Publication statusPublished - 2005

    Bibliographical note

    Version 2.0

    Keywords

    • Variable selection
    • Sparse
    • LASSO
    • LARS
    • Sparsity
    • SPCA
    • Matlab
    • Elastic Net

    Fingerprint

    Dive into the research topics of 'Matlab implementation of LASSO, LARS, the elastic net and SPCA'. Together they form a unique fingerprint.

    Cite this