\name{lasso.path.homotopy} \alias{lasso.path.homotopy} \title{computation of the LASSO path} \description{ Computes the complete LASSO regularization path by the homotopy method. } \usage{ lasso.path.homotopy(x, y, penalizations = NULL, min.lambda.ratio = 0.05) } \arguments{ \item{x}{ the design matrix. Rows are observations, lines are features. Must be stored by column (default in R). } \item{y}{ the response vector. } \item{penalizations}{ individual penalizations of features, or NULL. Must be nonnegative. } \item{min.lambda.ratio}{ the lowest value of the regularization parameter, as a ratio over the greatest one (null solution). } } \details{} \value{ list of records for each breakpoint of the path. Each item contains \item{lambda}{the regularization parameter} \item{t}{the corresponding L1 constraint, ie the L1 norm of the coefficient} \item{num_active}{the number of active features} \item{indices}{the indices of active features} \item{beta}{the coefficients of active features in the regularized solution} \item{beta.PLS}{the coefficients of active features in the partial least-square solution (least square on active features)} \item{hsr}{half squared residual: 0.5 * |y-x'beta|^2, for the regularized solution} \item{hsr.PLS}{half squared residual: 0.5 * |y-x'beta|^2, for the partial least-square solution} } \references{ } \author{ Manuel Loth } \note{ } %% ~Make other sections like Warning with \section{Warning }{....} ~ \seealso{ %% ~~objects to See Also as \code{\link{help}}, ~~~ \code{lasso.path.isolambda_descent} \code{lasso.path-package} } \examples{ ##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, ##-- or do help(data=index) for the standard data sets. ## The function is currently defined as function (x, y, penalizations = NULL, min.lambda.ratio = 0.05) { if (dim(x)[2] != length(y)) return x <- as.double(x) y <- as.double(y) if (!is.null(penalizations)) penalizations <- as.double(penalizations) r <- .Call("lasso_path_homotopy_R", x, y, penalizations, min.lambda.ratio) return(r) } } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{ ~kwd1 } \keyword{ ~kwd2 }% __ONLY ONE__ keyword per line