Description Usage Arguments Value See Also Examples
Produce a plot of the solution path of a quadrupen
fit.
1 2 3 4 
x 
output of a fitting procedure of the quadrupen
package ( 
y 
used for S4 compatibility. 
xvar 
variable to plot on the Xaxis: either 
main 
the main title. Default is set to the model name followed by what is on the Yaxis. 
log.scale 
logical; indicates if a logscale should be used
when 
standardize 
logical; standardize the coefficients before
plotting (with the norm of the predictor). Default is 
reverse 
logical; should the Xaxis be reversed when

labels 
vector indicating the names associated to the plotted
variables. When specified, a legend is drawn in order to identify
each variable. Only relevant when the number of predictor is
small. Remind that the intercept does not count. Default is

plot 
logical; indicates if the graph should be plotted on
call. Default is 
... 
Not used 
a ggplot2 object which can be plotted via the
print
method.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  ## Simulating multivariate Gaussian with blockwise correlation
## and piecewise constant vector of parameters
beta < rep(c(0,1,0,1,0), c(25,10,25,10,25))
cor < 0.75
Soo < toeplitz(cor^(0:(251))) ## Toeplitz correlation for irrelevant variables
Sww < matrix(cor,10,10) ## bloc correlation between active variables
Sigma < bdiag(Soo,Sww,Soo,Sww,Soo)
diag(Sigma) < 1
n < 50
x < as.matrix(matrix(rnorm(95*n),n,95) %*% chol(Sigma))
y < 10 + x %*% beta + rnorm(n,0,10)
## Plot the Lasso path
plot(elastic.net(x,y, lambda2=0), main="Lasso solution path")
## Plot the Elasticnet path
plot(elastic.net(x,y, lambda2=10), xvar = "lambda")
## Plot the Elasticnet path (fraction on Xaxis, unstandardized coefficient)
plot(elastic.net(x,y, lambda2=10), standardize=FALSE, xvar="fraction")
## Plot the Bounded regression path (fraction on Xaxis)
plot(bounded.reg(x,y, lambda2=10), xvar="fraction")

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