obj_function: Elastic net objective function value

In glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models

Elastic net objective function value

Description

Returns the elastic net objective function value.

Usage

obj_function(y, mu, weights, family, lambda, alpha, coefficients, vp)

Arguments

y	Quantitative response variable.
mu	Model's predictions for y.
weights	Observation weights.
family	A description of the error distribution and link function to be used in the model. This is the result of a call to a family function.
lambda	A single value for the lambda hyperparameter.
alpha	The elasticnet mixing parameter, with 0 \le \alpha \le 1.
coefficients	The model's coefficients (excluding intercept).
vp	Penalty factors for each of the coefficients.

glmnet documentation built on Aug. 22, 2023, 9:12 a.m.