cdfPen.fit {penalizedcdf} | R Documentation |
These are the fundamental computing algorithms that cdfPen invokes to estimate penalized linear models by varying lambda.
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)
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). |
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). |
Daniele Cuntrera, Luigi Augugliaro, Vito Muggeo
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