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)
Ldei(...)
# S3 method for lim
Ldei(lim, ...)
# S3 method for limfile
Ldei(file, verbose = TRUE, ...)
# S3 method for character
Ldei(...)
# S3 method for double
Ldei(...)a list containing:
vector containing the solution of the least distance problem.
vector containing the unconstrained solution of the least distance problem.
scalar, the sum of residuals of equalities and violated inequalities.
scalar, the value of the quadratic function at the solution.
logical, TRUE, if an error occurred.
ldei error text.
ldei.
a list that contains the linear inverse model
specification, as generated by function setup.limfile.
name of the inverse input file.
if TRUE: prints warnings and messages to the screen.
other arguments passed to function
ldei from packagelimSolve.
Karline Soetaert <karline.soetaert@nioz.nl>
Solves the following inverse problem: $$\min(\sum {Cost_i*x_i}^2)$$ subject to $$Ax=B$$ $$Gx>=H$$
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.