R/glmnetLRC-package.R

In pnnl/glmnetLRC: Lasso and Elastic-Net Logistic Regression Classification with an Arbitrary Loss Function

##' Lasso and elastic-net logistic regression classification with an arbitrary loss function
##'
##' Lasso and elastic-net logistic regression classification (LRC) with an arbitrary, discrete loss function
##' for the classification error
##'
##' \pkg{glmnetLRC} extends the \pkg{glmnet} package for training elastic-net LRCs with a user-specified
##' discrete loss function used to measure the classification error.  Tuning parameters are selected to
##' minimize the expected loss calculated by cross validation.  There are a handful of functions
##' you'll need (along with their associated methods): \code{\link{lossMatrix}}, \code{\link{glmnetLRC}}, 
##' and \code{\link{predict.glmnetLRC}}
##'
##' \tabular{ll}{
##' Package: \tab glmnetLRC\cr
##' Type: \tab Package\cr
##' Version: \tab 0.1.8\cr
##' Date: \tab 2016-07-01\cr
##' License: \tab file LICENSE\cr }
##'
##' @author Landon Sego, Alex Venzin, John Ramey
##' 
##' @docType package
##' 
##' @name glmnetLRC-package
##' 
##' @rdname glmnetLRC-package
##'
##' @importFrom graphics hist pairs par rect abline axis legend mtext plot text
##' @importFrom stats complete.cases median predict runif sd pbeta qbeta rnorm
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