Lasso {TraceAssist}

Logistic probability model via penalized maximum likelihood

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.