@MISC\{IMM2005-03897,
    author       = "K. Sj{\"{o}}strand",
    title        = "Matlab implementation of {LASSO,} {LARS,} the elastic net and {SPCA}",
    year         = "2005",
    month        = "jun",
    keywords     = "{LASSO,} {LARS,} {SPCA,} Matlab, Elastic Net, Sparse, Sparsity, Variable selection",
    publisher    = "Informatics and Mathematical Modelling, Technical University of Denmark, {DTU}",
    address      = "Richard Petersens Plads, Building 321, {DK-}2800 Kgs. Lyngby",
    note         = "Version 2.0",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/3897-full.html",
    abstract     = "UPDATE: Download the latest code and documentation from http://www.imm.dtu.dk/projects/spasm

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."
}