This function computes the coefficient matrix `B`

estimate, column-by-column. The observations of the data matrix `X`

are assumed to have zero mean.

1 | ```
DESP_SRL_B(X, lambda, solver = 'CD', sto = FALSE, nThreads = 1)
``` |

`X` |
The data matrix. |

`lambda` |
The penalization parameter that promotes sparsity. |

`solver` |
The solver. A string indicating the solver to use. `"CD"` specifies the coordinate descent algorithm; `"SCS"` specifies the free Splitting Conic Solver; `"Gurobi"` specifies the commercial Gurobi solver; `"Mosek"` specifies the commercial Mosek solver.
The default is |

`sto` |
Indicates whether a randomized algorithm (stochastic coordinate descent) have to be used when choosing the coordinate descent method, default FALSE. |

`nThreads` |
Set the number of threads for parallel processing when choosing the coordinate descent method or the SCS solver, default 1. |

The coefficient matrix.

Arnak Dalalyan and Samuel Balmand.

`sqR_Lasso`

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