cdfPen.fit: Fitter function for CDF penalty

In penalizedcdf: Estimate a Penalized Linear Model using the CDF Penalty Function

Fitter function for CDF penalty

Description

These are the fundamental computing algorithms that cdfPen invokes to estimate penalized linear models by varying lambda.

Usage

cdfPen.fit(b,
           b.tld,
           g,
           b.rho,
           H.rho,
           lmb.rho,
           nu,
           algorithm,
           nstep = 1E+5,
           eps = 1E-5,
           eps.lla = 1E-6,
           nstep.lla = 1E+5)

Arguments

b	Starting values of beta-vector.
b.tld	Starting values of sparse beta-vector.
g	Starting values of pseudo-variable.
b.rho	Ridge solution.
H.rho	Second part of ridge solution.
lmb.rho	Lambda-rho ratio.
nu	Shape parameter of the penalty. It affects the degree of the non-convexity of the penalty.
algorithm	Approximation to be used to obtain the sparse solution.
nstep	Maximum number of iterations of the global algorithm.
eps	Convergence threshold of the global algorithm.
eps.lla	Convergence threshold of the LLA-algorithm (if used).
nstep.lla	Maximum number of iterations of the LLA-algorithm (if used).

Value

b	Estimated beta-vector.
b.tld	Estimated sparse beta-vector.
g	Final values of pseudo-variable.
i	Number of iterations.
conv	Convergence check status (0 if converged).

Author(s)

Daniele Cuntrera, Luigi Augugliaro, Vito Muggeo

References

Aggiungere Arxiv

penalizedcdf documentation built on Feb. 16, 2023, 6:20 p.m.