coef.gaussian

An object with S3 class <code>"gaussian"</code>

object

The indices of the regularizaiton parameters in the solution path to be displayed. The default values are <code>c(1:3)</code>.

lambda.idx

The indices of the estimate regression coefficient vectors in the solution path to be displayed. The default values are <code>c(1:3)</code>.

beta.idx

Arguments to be passed to methods.

&#8230;

Extract estimated regression coefficient vectors from the solution path.

Computationally efficient tools for fitting generalized linear model with convex or non-convex penalty. Users can enjoy the superior statistical property of non-convex penalty such as SCAD and MCP which has significantly less estimation error and overfitting compared to convex penalty such as lasso and ridge. Computation is handled by multi-stage convex relaxation and the PathwIse CAlibrated Sparse Shooting algOrithm (PICASSO) which exploits warm start initialization, active set updating, and strong rule for coordinate preselection to boost computation, and attains a linear convergence to a unique sparse local optimum with optimal statistical properties. The computation is memory-optimized using the sparse matrix output.

coef.gaussian: Extract Model Coefficients for an object with S3 class `"gaussian"`

Description

Usage

Arguments

See Also