lsi_ln: Linear Least Squares with Inequality constraints, least norm...

In nlsic: Non Linear Least Squares with Inequality Constraints

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

nlsic documentation built on July 10, 2023, 2:03 a.m.