lsi_ln function

Linear Least Squares with Inequality constraints, least norm solution

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)

Arguments

• 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 %*% operation with a dense vector is defined
• x0: optional vector from which a least norm distance is searched for

Returns

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

See Also

lsi , ldp , base::qr