Description Usage Arguments Value References Examples
Implement DECODE
for sigma
and beta
to estimate Σ^1β where sigma
is an estimator of Σ and beta
is an estimator of β.
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sigma 
pxp positive semidefinite symmetric matrix. 
beta 
plength vector. 
lambda0 
number between 0 and 1. 
decode.tol 
error tolerance for 
decode.maxit 
maximum iterations for 
trace 
logical. If 
solver 
solver for l1RQP problem inside 
solver.tol 
tolerance for solver. 
solver.maxit 
maximum iterations for solver (only for APG). 
return.sigma 
logical. If 
return.beta 
logical. If 
return.param 
logical. If 
An object of class decode
containing:
eta 

theta 
final θ of the 
lambda 
final λ of the 
sigma.mult 
multiplier applied on 
total.iter 
number of iterations until convergence. 
call 
the matched call. 
method 
the solver used, if requested. 
lambda0 
the 
decode.tol 
the 
decode.maxit 
the 
trace 
the 
solver.tol 
the 
solver.maxit 
the 
eta.trace 
matrix of η used in each iteration, if requested. 
theta.trace 
vector of θ used in each iteration, if requested. 
lambda.trace 
vector of λ used in each iteration, if requested. 
Pun, C. S. (2018). A Sparse Learning Approach to RelativeVolatilityManaged Portfolio Selection. Hadimaja, M. Z., & Pun, C. S. (2018). A SelfCalibrated Regularized Direct Estimation for Graphical Selection and Discriminant Analysis.
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