lsi function

Linear Least Squares with Inequality constraints (LSI)

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

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

Returns

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

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

See Also

lsi_ln , ldp , base::qr