Description Usage Arguments Details Value Author(s) References See Also Examples
Solves a linear inverse model using least distance programming, i.e. minimizes the sum of squared unknowns.
Input presented either:
as matrices E, F, A, B, G, H (Ldei.double)
as a list (Ldei.lim) or
as a lim input file (Ldei.limfile)
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lim |
a list that contains the linear inverse model
specification, as generated by function |
file |
name of the inverse input file. |
verbose |
if |
... |
other arguments passed to function
|
Solves the following inverse problem:
\min(∑ {Cost_i*x_i}^2)
subject to
Ax=B
Gx>=H
a list containing:
X |
vector containing the solution of the least distance problem. |
unconstrained.Solution |
vector containing the unconstrained solution of the least distance problem. |
residualNorm |
scalar, the sum of residuals of equalities and violated inequalities. |
solutionNorm |
scalar, the value of the quadratic function at the solution. |
IsError |
logical, |
Error |
ldei error text. |
type |
ldei. |
Karline Soetaert <karline.soetaert@nioz.nl>
Lawson C.L.and Hanson R.J. 1974. SOLVING LEAST SQUARES PROBLEMS, Prentice-Hall
Lawson C.L.and Hanson R.J. 1995. Solving Least Squares Problems. SIAM classics in applied mathematics, Philadelphia. (reprint of book)
ldei
, the more general function from package limSolve.
Linp
, to solve the linear inverse problem by linear programming.
Lsei
, to solve the linear inverse problem by lsei (least
squares with equality and inequality constraints).
function ldei
from packagelimSolve
.
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