b_update2: Update beta estimates using L-BFGS-B
In theandyb/aeffp: Lasso-penalized Logistic Regression via ADMM
Description
Usage
Arguments
Value
Description
The beta-update step requires optimizing a convex function. This version of the update function
uses R's built-it optim function to do this for us
Usage
1
b_update2(X, y, u, z, rho)
Arguments
X
Covariate matrix (no column for intercept)
y
Vector of observations (coded in -1/1)
u
Current value of u vector (ADMM optimization)
z
Current value of z vector (ADMM optimization)
rho
Tuning parameter for ADMM optimization
Value
Vector containing updated estimate of beta vector
theandyb/aeffp documentation built on May 8, 2019, 9:09 a.m.
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Description Usage Arguments Value
Description
The beta-update step requires optimizing a convex function. This version of the update function uses R's built-it optim function to do this for us
Usage
1 | b_update2(X, y, u, z, rho)
|
Arguments
X |
Covariate matrix (no column for intercept) |
y |
Vector of observations (coded in -1/1) |
u |
Current value of u vector (ADMM optimization) |
z |
Current value of z vector (ADMM optimization) |
rho |
Tuning parameter for ADMM optimization |
Value
Vector containing updated estimate of beta vector
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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