inst/doc/getting-started.R

In ncvreg: Regularization Paths for SCAD and MCP Penalized Regression Models

## ----setup, include=FALSE-----------------------------------------------------
library(ncvreg)
set.seed(4)
knitr::opts_knit$set(aliases=c(h = 'fig.height', w = 'fig.width'))
knitr::opts_chunk$set(comment="#", collapse=TRUE, cache=FALSE, tidy=FALSE)
knitr::knit_hooks$set(small.mar = function(before, options, envir) {
  if (before) par(mar = c(4, 4, .1, .1))
})

## ----prostate-----------------------------------------------------------------
data(Prostate)
X <- Prostate$X
y <- Prostate$y

## ----fit----------------------------------------------------------------------
fit <- ncvreg(X, y)

## ----plot, h=4, w=6, small.mar=TRUE-------------------------------------------
plot(fit)

## ----coef---------------------------------------------------------------------
coef(fit, lambda=0.05)

## ----summary, output.lines=1:5------------------------------------------------
summary(fit, lambda=0.05)

## ----cvplot, h=5, w=6---------------------------------------------------------
cvfit <- cv.ncvreg(X, y)
summary(cvfit)
plot(cvfit)

## ----cvcoef-------------------------------------------------------------------
coef(cvfit)

## ----predict------------------------------------------------------------------
predict(cvfit, X=head(X))     # Prediction of response for new observations
predict(cvfit, type="nvars")  # Number of nonzero coefficients
predict(cvfit, type="vars")   # Identity of the nonzero coefficients