The function may be called by the names: e02gcc, nag_fit_glin_linf or nag_linf_fit.
Given a matrix with rows and columns and a vector with elements, the function calculates an solution to the overdetermined system of equations
That is to say, it calculates a vector , with elements, which minimizes the norm of the residuals (the absolutely largest residual)
where the residuals are given by
Here is the element in row and column of , is the th element of and the th element of . The matrix need not be of full rank. The solution is not unique in this case, and may not be unique even if is of full rank.
Alternatively, in applications where a complete minimization of the norm is not necessary, you may obtain an approximate solution, usually in shorter time, by giving an appropriate value to the argument relerr.
Typically in applications to data fitting, data consisting of points with coordinates is to be approximated in the norm by a linear combination of known functions ,
This is equivalent to finding an solution to the overdetermined system of equations
Thus if, for each value of and the element of the matrix above is set equal to the value of and is set equal to , the solution vector will contain the required values of the . Note that the independent variable above can, instead, be a vector of several independent variables (this includes the case where each is a function of a different variable, or set of variables).
The algorithm is a modification of the simplex method of linear programming applied to the dual formation of the problem (see Barrodale and Phillips (1974) and Barrodale and Phillips (1975)). The modifications are designed to improve the efficiency and stability of the simplex method for this particular application.
Barrodale I and Phillips C (1974) An improved algorithm for discrete Chebyshev linear approximation Proc. 4th Manitoba Conf. Numerical Mathematics 177–190 University of Manitoba, Canada
Barrodale I and Phillips C (1975) Solution of an overdetermined system of linear equations in the Chebyshev norm [F4] (Algorithm 495) ACM Trans. Math. Software1(3) 264–270
1: – Nag_OrderTypeInput
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by . See Section 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.
2: – IntegerInput
On entry: the number of equations, (the number of rows of the matrix ).
3: – IntegerInput
On entry: the number of unknowns, (the number of columns of the matrix ).
4: – doubleInput/Output
Note: the dimension, dim, of the array
must be at least
where appears in this document, it refers to the array element
On entry: must contain , the element in the th row and th column of the matrix , for and , (that is, the transpose of the matrix). The remaining elements need not be set. Preferably, the columns of the matrix (rows of the argument a) should be scaled before entry: see Section 7.
On exit: contains the last simplex tableau.
5: – doubleInput/Output
On entry: must contain , the th element of the vector , for .
On exit: the
th residual corresponding to the solution vector , for . Note however that these residuals may contain few significant figures, especially when resmax is within one or two orders of magnitude of tol. Indeed if , the elements may all be set to zero. It is, therefore, often advisable to compute the residuals directly.
6: – doubleInput
On entry: a threshold below which numbers are regarded as zero. The recommended threshold value is , where is the machine precision. If on entry, the recommended value is used within the function. If premature termination occurs, a larger value for tol may result in a valid solution.
7: – double *Input/Output
On entry: must be set to a bound on the relative error acceptable in the maximum residual at the solution.
If , the solution is computed, and relerr is set to on exit.
If , the function obtains instead an approximate solution for which the largest residual is less than times that of the solution; on exit, relerr contains a smaller value such that the above bound still applies. (The usual result of this option, say with , is a saving in the number of simplex iterations).
On exit: is altered as described above.
8: – doubleOutput
On exit: if an optimal but not necessarily unique solution is found,
contains the th element of the solution vector , for . Whether this is an solution or an approximation to one, depends on the value of relerr on entry.
9: – double *Output
On exit: if an optimal but not necessarily unique solution is found, resmax contains the absolute value of the largest residual(s) for the solution vector . (See b.)
10: – Integer *Output
On exit: if an optimal but not necessarily unique solution is found, rank contains the computed rank of the matrix .
11: – Integer *Output
On exit: if an optimal but not necessarily unique solution is found, iter contains the number of iterations taken by the simplex method.
12: – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
On entry, argument had an illegal value.
On entry, .
On entry, and .
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
An optimal solution has been obtained, but may not be unique.
Premature termination due to rounding errors. Try using larger value of tol: .
Experience suggests that the computational accuracy of the solution is comparable with the accuracy that could be obtained by applying Gaussian elimination with partial pivoting to the equations which have residuals of largest absolute value. The accuracy, therefore, varies with the conditioning of the problem, but has been found generally very satisfactory in practice.
8Parallelism and Performance
e02gcc is not threaded in any implementation.
The effects of and on the time and on the number of iterations in the simplex method vary from problem to problem, but typically the number of iterations is a small multiple of and the total time is approximately proportional to .
It is recommended that, before the function is entered, the columns of the matrix are scaled so that the largest element in each column is of the order of unity. This should improve the conditioning of the matrix, and also enable the argument tol to perform its correct function. The solution obtained will then, of course, relate to the scaled form of the matrix. Thus if the scaling is such that, for each , the elements of the th column are multiplied by the constant , the element of the solution vector must be multiplied by if it is desired to recover the solution corresponding to the original matrix .
This example approximates a set of data by a curve of the form
where , and are unknown. Given values at points we may form the overdetermined set of equations for , and