Ldei {LIM}R Documentation

Solves a linear inverse model using least distance programming

Description

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)

    Usage

    Ldei(...)
    Ldei.lim(lim,...)
    Ldei.limfile(file, verbose=TRUE, ...)
    Ldei.character(...)
    Ldei.double(...)

    Arguments

    lim a list that contains the linear inverse model specification, as generated by function Setup
    file name of the inverse input file
    verbose if TRUE: prints warnings and messages to the screen
    ... other arguments passed to function ldei from packagelimSolve

    Details

    Solves the following inverse problem:

    min(sum {Cost_i*x_i}^2)

    subject to

    Ax=B

    Gx>=H

    Value

    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 TRUE, if an error occurred
    Error ldei error text
    type ldei

    Author(s)

    Karline Soetaert <k.soetaert@nioo.knaw.nl>

    References

    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)

    See Also

    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

    Examples

    Ldei(LIMRigaAutumn)

    [Package LIM version 1.1 Index]