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| author | Gertjan van den Burg <burg@ese.eur.nl> | 2017-01-25 14:03:38 +0100 |
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| committer | Gertjan van den Burg <burg@ese.eur.nl> | 2017-01-25 14:03:38 +0100 |
| commit | 96e7bc6fdf292c7f73e599dae0b7957161e15212 (patch) | |
| tree | 1bedb98795b657ce51be2a6a79da7fe69435b00a /man/sparsestep-package.Rd | |
| parent | Add author and reference to each public method documentation (diff) | |
| download | sparsestep-96e7bc6fdf292c7f73e599dae0b7957161e15212.tar.gz sparsestep-96e7bc6fdf292c7f73e599dae0b7957161e15212.zip | |
Various documentation fixes
Diffstat (limited to 'man/sparsestep-package.Rd')
| -rw-r--r-- | man/sparsestep-package.Rd | 35 |
1 files changed, 23 insertions, 12 deletions
diff --git a/man/sparsestep-package.Rd b/man/sparsestep-package.Rd index 67ca27d..9bf2144 100644 --- a/man/sparsestep-package.Rd +++ b/man/sparsestep-package.Rd @@ -1,39 +1,50 @@ -% Generated by roxygen2 (4.1.1): do not edit by hand +% Generated by roxygen2: do not edit by hand % Please edit documentation in R/sparsestep-package.R \docType{package} \name{sparsestep-package} \alias{sparsestep-package} \title{SparseStep: Approximating the Counting Norm for Sparse Regularization} \description{ -In the SparseStep regression model the ordinary least-squares problem is -augmented with an approximation of the exact \eqn{\ell_0}{l[0]} pseudonorm. -This approximation is made increasingly more accurate in the SparseStep -algorithm, resulting in a sparse solution to the regression problem. See +In the SparseStep regression model the ordinary least-squares problem is +augmented with an approximation of the exact \eqn{\ell_0}{l[0]} pseudonorm. +This approximation is made increasingly more accurate in the SparseStep +algorithm, resulting in a sparse solution to the regression problem. See the references for more information. } \section{SparseStep functions}{ The main SparseStep functions are: \describe{ -\item{\code{\link{sparsestep}}}{Fit a SparseStep model for a given range of +\item{\code{\link{sparsestep}}}{Fit a SparseStep model for a given range of \eqn{\lambda} values} -\item{\code{\link{path.sparsestep}}}{Fit the SparseStep model along a path -of \eqn{\lambda} values which are generated such that a model is created at -each possible level of sparsity, or until a given recursion depth is +\item{\code{\link{path.sparsestep}}}{Fit the SparseStep model along a path +of \eqn{\lambda} values which are generated such that a model is created at +each possible level of sparsity, or until a given recursion depth is reached.} } Other available functions are: \describe{ -\item{\code{\link{plot}}}{Plot the coefficient path of the SparseStep +\item{\code{\link{plot}}}{Plot the coefficient path of the SparseStep model.} -\item{\code{\link{predict}}}{Predict the outcome of the linear model using +\item{\code{\link{predict}}}{Predict the outcome of the linear model using SparseStep} \item{\code{\link{coef}}}{Get the coefficients from the SparseStep model} -\item{\code{\link{print}}}{Print a short description of the SparseStep +\item{\code{\link{print}}}{Print a short description of the SparseStep model} } } +\examples{ +x <- matrix(rnorm(100*20), 100, 20) +y <- rnorm(100) +fit <- sparsestep(x, y) +plot(fit) +fits <- path.sparsestep(x, y) +plot(fits) +x2 <- matrix(rnorm(50*20), 50, 20) +y2 <- predict(fits, x2) + +} \author{ Gerrit J.J. van den Burg, Patrick J.F. Groenen, Andreas Alfons\cr Maintainer: Gerrit J.J. van den Burg <gertjanvandenburg@gmail.com> |
