Compositional (version 5.5)

Plot of the LASSO coefficients: Plot of the LASSO coefficients

Description

Plot of the LASSO coefficients.

Usage

lassocoef.plot(lasso, lambda = TRUE)

Arguments

lasso

An object where you have saved the result of the LASSO regression. See the examples for more details.

lambda

If you want the x-axis to contain the logarithm of the penalty parameter \(\log(\lambda)\) set this to TRUE. Otherwise the x-axis will contain the \(L_1\)-norm of the coefficients.

Value

A plot of the \(L_2\)-norm of the coefficients of each predictor variable (y-axis) versus the \(L_1\)-norm of all the coefficients (x-axis).

Details

This function plots the \(L_2\)-norm of the coefficients of each predictor variable versus the \(\log(\lambda)\) or the \(L_1\)-norm of the coefficients. This is the same plot as the one produced by the glmnet package with type.coef = "2norm".

References

Friedman, J., Hastie, T. and Tibshirani, R. (2010) Regularization Paths for Generalized Linear Models via Coordinate Descent. Journal of Statistical Software, Vol. 33(1), 1-22.

See Also

lasso.klcompreg, cv.lasso.klcompreg, lasso.compreg, cv.lasso.compreg, kl.compreg, comp.reg

Examples

# NOT RUN {
y <- as.matrix(iris[, 1:4])
y <- y / rowSums(y)
x <- matrix( rnorm(150 * 30), ncol = 30 )
a <- lasso.klcompreg(y, x)
lassocoef.plot(a)
b <- lasso.compreg(y, x)
lassocoef.plot(b)
# }