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MFKnockoffs (version 0.9.1)

MFKnockoffs.knocks.solve_equi: Optimization for equi-correlated knockoffs

Description

Solves the optimization problem needed to create equi-correlated knockoffs

Usage

MFKnockoffs.knocks.solve_equi(Sigma)

Arguments

Sigma

A positive-definite covariance matrix

Value

The solution \(s\) to the semidefinite programming problem defined above

Details

Computes the closed-form solution to the semidefinite programming problem: $$ \mathrm{maximize} \; s \quad \mathrm{subject} \; \mathrm{to:} \; 0 <= s <= 1, \; 2\Sigma - sI >= 0 $$ used to generate equi-correlated knockoffs.

The closed form-solution to this problem is \(s = 2\lambda_{\mathrm{min}}(\Sigma) \land 1\)

See Also

Other Optimize knockoffs: MFKnockoffs.knocks.solve_asdp, MFKnockoffs.knocks.solve_sdp