lsi_ln {nlsic}

Linear Least Squares with Inequality constraints, least norm solution

Description

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.

Usage

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

Value

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

See Also

lsi, ldp, base::qr