get_grad_f: Calculate the gradient for one step
In krisrs1128/gflasso: Perform graph structured multitask regression, according to Chen, et al.
get_grad_f R Documentation
Calculate the gradient for one step
Description
Calculate the gradient for one step
Usage
get_grad_f(X, Y, W, C, mu)
Arguments
X
The data matrix.
Y
The matrix of regression responses.
C
The L1 penalization matrix, returned by get_C().
mu
The smoothing parameter.
B
The J x K regression coefficient estimates.
Value
The gradient descent direction for B, given the current estimates.
See equation (11) in the reference.
References
Smoothing Proximal Gradient Method for General Structured Sparse Regressoin
krisrs1128/gflasso documentation built on Nov. 11, 2023, 4:24 a.m.
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| get_grad_f | R Documentation |
Calculate the gradient for one step
Description
Calculate the gradient for one step
Usage
get_grad_f(X, Y, W, C, mu)
Arguments
X |
The data matrix. |
Y |
The matrix of regression responses. |
C |
The L1 penalization matrix, returned by |
mu |
The smoothing parameter. |
B |
The J x K regression coefficient estimates. |
Value
The gradient descent direction for B, given the current estimates. See equation (11) in the reference.
References
Smoothing Proximal Gradient Method for General Structured Sparse Regressoin
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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