plot.corrected_lasso: plot.corrected_lasso

In hdme: High-Dimensional Regression with Measurement Error

plot.corrected_lasso

Description

Plot the output of corrected_lasso

Usage

## S3 method for class 'corrected_lasso'
plot(x, type = "nonzero", label = FALSE, ...)

Arguments

x	Object of class corrected_lasso, returned from calling corrected_lasso()
type	Type of plot. Either "nonzero" or "path". Ignored if length(x$radii) == 1, in case of which all coefficient estimates are plotted at the given regularization parameter.
label	Logical specifying whether to add labels to coefficient paths. Only used when type = "path".
...	Other arguments to plot (not used)

Examples

# Example with linear regression
n <- 100 # Number of samples
p <- 50 # Number of covariates
# True (latent) variables
X <- matrix(rnorm(n * p), nrow = n)
# Measurement error covariance matrix
# (typically estimated by replicate measurements)
sigmaUU <- diag(x = 0.2, nrow = p, ncol = p)
# Measurement matrix (this is the one we observe)
W <- X + rnorm(n, sd = sqrt(diag(sigmaUU)))
# Coefficient
beta <- c(seq(from = 0.1, to = 1, length.out = 5), rep(0, p-5))
# Response
y <- X %*% beta + rnorm(n, sd = 1)
# Run the corrected lasso
fit <- corrected_lasso(W, y, sigmaUU, family = "gaussian")
plot(fit)

hdme documentation built on May 31, 2023, 5:44 p.m.