lsi_ln | R Documentation |

solve linear least square problem `min_x ||A*x-b||`

with inequality constraints `u%*%x >= co`

If A is rank deficient, least norm solution `||mnorm%*%(x-x0)||`

is used.
If the parameter mnorm is NULL, it is treated as an identity matrix.
If the vector x0 is NULL, it is treated as 0 vector.

```
lsi_ln(a, b, u = NULL, co = NULL, rcond = 1e+10, mnorm = NULL, x0 = NULL)
```

`a` |
dense matrix A or its QR decomposition |

`b` |
right hand side vector |

`u` |
dense matrix of inequality constraints |

`co` |
right hand side vector of inequality constraints |

`rcond` |
maximal condition number for determining rank deficient matrix |

`mnorm` |
norm matrix (can be dense or sparse) for which |

`x0` |
optional vector from which a least norm distance is searched for |

solution vector whose attribute 'mes' may contain a message about possible numerical problems

lsi, ldp, base::qr

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