coefpath

Visualize the coefficient path resulting from the elastic net

coefpath(model, ...)

# S3 method for glmnet
coefpath(model, xlab = "Log Lambda", ylab = "Coefficients",
  showLegend = c("onmouseover", "auto", "always", "follow", "never"),
  annotate = TRUE, elementID = NULL, ...)

# S3 method for cv.glmnet
coefpath(model, xlab = "Log Lambda",
  ylab = "Coefficients", showLegend = c("onmouseover", "auto", "always",
  "follow", "never"), annotate = TRUE, colorMin = "black",
  strokePatternMin = "dotted", labelMin = "lambda.min",
  locMin = c("bottom", "top"), color1se = "black",
  strokePattern1se = "dotted", label1se = "lambda.1se",
  loc1se = c("bottom", "top"), ...)

Arguments

model	A glmnet model
...	Arguments passed on to extractPath
xlab	x-axis label
ylab	y-axis label
showLegend	When to display the legend. Specify "always" to always show the legend. Specify "onmouseover" to only display it when a user mouses over the chart. Specify "follow" to have the legend show as overlay to the chart which follows the mouse. The default behavior is "auto", which results in "always" when more than one series is plotted and "onmouseover" when only a single series is plotted.
annotate	If TRUE (default) plot the name of the series
elementID	Unique identified for dygraph, if NULL it will be randomly generated
colorMin	Color for line showing lambda.min
strokePatternMin	Stroke pattern for line showing lambda.min
labelMin	Label for line showing lambda.min
locMin	Location for line showing lambda.min, can be 'bottom' or 'top'
color1se	Color for line showing lambda.1se
strokePattern1se	Stroke pattern for line showing lambda.1se
label1se	Label for line showing lambda.1se
loc1se	Location for line showing lambda.1se, can be 'bottom' or 'top'

Value

A dygraphs object

Details

This is a replacement plot for visualizing the coefficient path resulting from the elastic net. This allows for interactively inspecting the plot so it is easier to disambiguate the coefficients.

Examples

library(glmnet)
#> Loading required package: Matrix
#> Loaded glmnet 3.0-1
library(ggplot2)
library(useful)
data(diamonds)
diaX <- useful::build.x(price ~ carat + cut + x - 1, data=diamonds, contrasts = TRUE)
diaY <- useful::build.y(price ~ carat + cut + x - 1, data=diamonds)
modG1 <- glmnet(x=diaX, y=diaY)
coefpath(modG1)
#> Registered S3 method overwritten by 'xts':
#>   method     from
#>   as.zoo.xts zoo 

modG2 <- cv.glmnet(x=diaX, y=diaY, nfolds=5)
coefpath(modG2)

x <- matrix(rnorm(100*20),100,20)
y <- rnorm(100)
fit1 <- glmnet(x, y)
coefpath(fit1)