Lasso: Logistic probability model via penalized maximum likelihood

In TraceAssist: Nonparametric Trace Regression via Sign Series Representation

Description

Fit a logistic probability model based on Lasso penalty

Usage

Lasso(xvec,y,xnew,lambda)

Arguments

xvec	An input matrix. Each row is a vectorized predictor.
y	Binary response variable.
xnew	New predictors in the test data. Organized as a matrix with each row being a data point.
lambda	The regularization penalty.

Value

The returned object is a list of components.

B_est - The estimated coefficient vector of linear predictor.

prob - The predicted probabilities for the test data.

TraceAssist documentation built on May 10, 2021, 9:07 a.m.