plot.sgl {dfr}R Documentation

Plot models of the following object types: "sgl", "sgl_cv".

Description

Plots the pathwise solution of a cross-validation fit, from a call to one of the following: dfr_sgl(), dfr_sgl.cv(), dfr_adap_sgl(), dfr_adap_sgl.cv().

Usage

## S3 method for class 'sgl'
plot(x, how_many = 10, ...)

Arguments

x

Object of one of the following classes: "sgl", "sgl_cv"..

how_many

Defines how many predictors to plot. Plots the predictors in decreasing order of largest absolute value.

...

further arguments passed to base function.

Value

A list containing:

response

The predicted response. In the logistic case, this represents the predicted class probabilities.

class

The predicted class assignments. Only returned if type = "logistic" in the model object.

See Also

dfr_sgl(), dfr_sgl.cv(), dfr_adap_sgl(), dfr_adap_sgl.cv()

Other SGL-methods: dfr_adap_sgl(), dfr_adap_sgl.cv(), dfr_sgl(), dfr_sgl.cv(), predict.sgl(), print.sgl()

Examples

# specify a grouping structure
groups = c(1,1,2,2,3)
# generate data
data = sgs::gen_toy_data(p=5, n=4, groups = groups, seed_id=3,signal_mean=20,group_sparsity=1)
# run DFR-SGL
model = dfr_sgl(X = data$X, y = data$y, groups=groups, type = "linear", 
path_length = 20, alpha = 0.95, 
min_frac = 0.05, standardise="l2",intercept=TRUE,verbose=FALSE)
plot(model, how_many = 10)

[Package dfr version 0.1.5 Index]