lsi: Linear Least Squares with Inequality constraints (LSI)

lsiR Documentation

Linear Least Squares with Inequality constraints (LSI)

Description

solve linear least square problem (min ||A%%x-b||) with inequality constraints u%%x>=co

Usage

lsi(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. Rows containing NA are dropped.

u

dense matrix of inequality constraints

co

right hand side vector of inequality constraints

rcond

maximal condition number for determining rank deficient matrix

mnorm

dummy parameter

x0

dummy parameter

Details

Method:

  1. reduce the problem to ldp (min(xat*xa) => least distance programming)

  2. solve ldp

  3. change back to x
    If b is all NA, then a vector of NA is returned.

mnrom, and x0 are dummy parameters which are here to make lsi() compatible with lsi_ln() argument list

Value

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

See Also

lsi_ln, ldp, base::qr


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

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