huber: Huber Function

In CVXR: Disciplined Convex Optimization

Huber Function

Description

The elementwise Huber function, Huber(x, M) = 1

2M|x|-M^2

for |x| \geq |M|

|x|^2

for |x| \leq |M|.

Usage

huber(x, M = 1)

Arguments

x	An Expression, vector, or matrix.
M	(Optional) A positive scalar value representing the threshold. Defaults to 1.

Value

An Expression representing the Huber function evaluated at the input.

Examples

set.seed(11)
n <- 10
m <- 450
p <- 0.1    # Fraction of responses with sign flipped

# Generate problem data
beta_true <- 5*matrix(stats::rnorm(n), nrow = n)
X <- matrix(stats::rnorm(m*n), nrow = m, ncol = n)
y_true <- X %*% beta_true
eps <- matrix(stats::rnorm(m), nrow = m)

# Randomly flip sign of some responses
factor <- 2*rbinom(m, size = 1, prob = 1-p) - 1
y <- factor * y_true + eps

# Huber regression
beta <- Variable(n)
obj <- sum(huber(y - X %*% beta, 1))
prob <- Problem(Minimize(obj))
result <- solve(prob)
result$getValue(beta)

CVXR documentation built on June 27, 2024, 5:11 p.m.