casl_lenet: Compute linear elastic net using coordinate descent.

In BillyTian/bis557: Package containing assignments, projects or other products in BIS557

Description

Compute linear elastic net using coordinate descent.

Usage

casl_lenet(X, y, lambda, alpha = 1, b = matrix(0, nrow = ncol(X), ncol
  = 1), tol = 1e-05, maxit = 50L, W = rep(1, length(y))/length(y))

Arguments

X	A numeric data matrix.
y	Response vector.
lambda	The penalty term.
alpha	Value from 0 and 1; balance between l1/l2 penalty.
b	Current value of the regression vector.
tol	Numeric tolerance parameter.
maxit	Integer maximum number of iterations.
W	Vector of sample weights.

Value

Regression vector beta of length ncol(X).

Author(s)

Taylor Arnold, Michael Kane, Bryan Lewis.

References

Taylor Arnold, Michael Kane, and Bryan Lewis. A Computational Approach to Statistical Learning. Chapman & Hall/CRC Texts in Statistical Science, 2019.

BillyTian/bis557 documentation built on Dec. 19, 2020, 7:30 a.m.