MFKnockoffs.knocks.solve_equi: Optimization for equi-correlated knockoffs
In MFKnockoffs: Model-Free Knockoff Filter for Controlled Variable Selection
Description
Usage
Arguments
Details
Value
See Also
Description
Solves the optimization problem needed to create equi-correlated knockoffs
Usage
1
Arguments
Sigma
A positive-definite covariance matrix
Details
Computes the closed-form solution to the semidefinite programming problem:
\mathrm{maximize} \; s \quad
\mathrm{subject} \; \mathrm{to:} \; 0 <= s <= 1, \;
2Σ - sI >= 0
used to generate equi-correlated knockoffs.
The closed form-solution to this problem is s = 2λ_{\mathrm{min}}(Σ) \land 1
Value
The solution s to the semidefinite programming problem defined above
See Also
Other Optimize knockoffs: MFKnockoffs.knocks.solve_asdp,
MFKnockoffs.knocks.solve_sdp
MFKnockoffs documentation built on May 2, 2019, 6:33 a.m.
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Description Usage Arguments Details Value See Also
Description
Solves the optimization problem needed to create equi-correlated knockoffs
Usage
1 |
Arguments
Sigma |
A positive-definite covariance matrix |
Details
Computes the closed-form solution to the semidefinite programming problem:
\mathrm{maximize} \; s \quad \mathrm{subject} \; \mathrm{to:} \; 0 <= s <= 1, \; 2Σ - sI >= 0
used to generate equi-correlated knockoffs.
The closed form-solution to this problem is s = 2λ_{\mathrm{min}}(Σ) \land 1
Value
The solution s to the semidefinite programming problem defined above
See Also
Other Optimize knockoffs: MFKnockoffs.knocks.solve_asdp,
MFKnockoffs.knocks.solve_sdp
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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