CQRPADMMCPP: Composite Quantile Regression (cqr) with Adaptive Lasso...
In cqrReg: Quantile, Composite Quantile Regression and Regularized Versions
CQRPADMMCPP R Documentation
Composite Quantile Regression (cqr) with Adaptive Lasso Penalty (lasso) use Alternating Direction Method of Multipliers (ADMM) algorithm core computational part
Description
The adaptive lasso parameter base on the estimated coefficient without penalty function.
Composite quantile regression find the estimated coefficient which minimize the absolute error for various quantile level.
The problem is well suited to distributed convex optimization and is based on Alternating Direction Method of Multipliers (ADMM) algorithm .
cqrReg documentation built on June 7, 2022, 9:06 a.m.
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| CQRPADMMCPP | R Documentation |
Composite Quantile Regression (cqr) with Adaptive Lasso Penalty (lasso) use Alternating Direction Method of Multipliers (ADMM) algorithm core computational part
Description
The adaptive lasso parameter base on the estimated coefficient without penalty function. Composite quantile regression find the estimated coefficient which minimize the absolute error for various quantile level. The problem is well suited to distributed convex optimization and is based on Alternating Direction Method of Multipliers (ADMM) algorithm .
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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