Description Usage Arguments Details Value See Also

Applies Alternating Direction Method of Multipliers to the l1-regularized quadratic program

*f(x) + g(x) = 0.5*x^T*A*x - d^T*x + lambda*|x|_l1*

1 | ```
ADMM_EN_SMW(Ainv, V, R, d, x0, lam, mu, maxits, tol, quiet)
``` |

`Ainv` |
Diagonal of |

`V` |
Matrix from SMW formula. |

`R` |
Upper triangular matrix in Cholesky decomposition of |

`d` |
nx1 dimensional column vector. |

`lam` |
Regularization parameter for l1 penalty, must be greater than zero. |

`mu` |
Augmented Lagrangian penalty parameter, must be greater than zero. |

`maxits` |
Number of iterations to run |

`tol` |
Vector of stopping tolerances, first value is absolute, second is relative tolerance. |

`quiet` |
Logical controlling display of intermediate statistics. |

`alpha` |
Step length. |

This function is used by other functions and should only be called explicitly for debugging purposes.

`ADMM_EN_SMW`

returns an object of `class`

"`ADMM_EN_SMW`

" including a list
with the following named components

`call`

The matched call.

`x`

Found solution.

`y`

Dual solution.

`z`

Slack variables.

`k`

Number of iterations used.

Used by: `SDAD`

and the `SDADcv`

cross-validation version.

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