IMSL_QRSOL

The IMSL_QRSOL function solves a real linear least-squares problem Ax = b.

Note
This routine requires an IDL Advanced Math and Stats license. For more information, contact your ITT Visual Information Solutions sales or technical support representative.

Syntax

Result = IMSL_QRSOL(b[, a] [, AUXQR=variable] [, BASIS=variable]
[, /DOUBLE] [, QR=variable] [, PIVOT=variable] [, RESIDUAL=variable] [, TOLERANCE=value])

Return Value

The solution, x, of the linear least-squares problem Ax = b.

Arguments

b

Matrix containing the right-hand side.

a

(Optional) Two-dimensional matrix containing the coefficient matrix. Element A (i, j) contains the j-th coefficient of the i-th equation.

Keywords

AUXQR

Named variable in which the matrix containing the scalars τ_k of the Householder transformations that define the decomposition, as computed in the IMSL_QRFAC procedure, is stored. The AUXQR, PIVOT, and QR keywords must be used together.

BASIS

Named variable containing an integer specifying the number of columns used in the solution. The value BASIS = k, if |r_k,k| < TOLERANCE*|r_0,0| and |r_i,i| ≥ TOLERANCE*|r_0,0| for i = 0, 1, ..., k – 1. For more information on the use of this option, see Discussion.

DOUBLE

If present and nonzero, double precision is used.

QR

Named variable which stores the matrix containing Householder transformations that define the decomposition, as computed in the IMSL_QRFAC procedure. The AUXQR, PIVOT, and QR keywords must be used together.

PIVOT

Named variable in which the array containing the desired variable order and usage information is stored. The AUXQR, PIVOT, and QR keywords must be used together.

On input, if PIVOT (k) > 0, then column k of A is an initial column. If PIVOT (k) = 0, then the column of A is a free column and can be interchanged in the column pivoting. If PIVOT (k) < 0, then column k of A is a final column. If all columns are specified as initial (or final) columns, then no pivoting is performed. (The permutation matrix P is the identity matrix in this case.)

On output, PIVOT (k) contains the index of the column of the original matrix that has been interchanged into column k.

Default: PIVOT (*) = 0

Note
If IMSL_QRSOL is used to solve a problem previously factored in IMSL_QRFAC, the matrix specified by PIVOT should contain the same information that the IMSL_QRFAC parameter PIVOT contained upon output.

RESIDUAL

Named variable in which the matrix containing the residual vector b – Ax is stored.

TOLERANCE

Nonnegative tolerance used to determine the subset of columns of A to be included in the solution. Default: TOLERANCE = SQRT(ε), where ε is machine precision

Discussion

IMSL_QRSOL solves a system of linear least-squares problems Ax = b with column pivoting. It computes a QR factorization of the matrix AP, where P is the permutation matrix defined by the pivoting, and computes the smallest integer k satisfying |r_k,k| < TOLERANCE*|r_0,0| to the output keyword BASIS.

Householder transformations:

Q_k = I – τ_ku_ku_k^T, k = 0, ..., min(m – 1, n) – 1

compute the factorization. The decomposition is computed in the form Q_{min (m – 1, n) – 1}... Q₀ AP = R, so AP = QR where Q = Q₀... Q_{min (m – 1, n) – 1}. Since each Householder vector u_k has zeros in the first k + 1 entries, it is stored as part of column k of QR. The upper-trapezoidal matrix R is stored in the upper-trapezoidal part of the first min(m, n) rows of QR. The solution x to the least-squares problem is computed by solving the upper-triangular system of linear equations R (0:k, 0:k) y (0:k) = (Q^Tb) (0:k) with k = Basis – 1. The solution is completed by setting y (k:n – 1) to zero and rearranging the variables, x = Py.

If the QR and AUXQR keywords are specified, then the function computes the least-squares solution to Ax = b given the QR factorization previously defined. There are Basis columns used in the solution. Hence, in the case that all columns are free, x is computed as described in the default case.

Example

This example illustrates the least-squares solution of four linear equations in three unknowns by using column pivoting. This is equivalent to least-squares quadratic polynomial fitting to four data values. The polynomial is written as p(t) = x₀ + tx₁ + t²x₂ and the data pairs (t_i, b_i), t_i = 2(i + 1), i = 0, 1, 2, 3. The solution to Ax = b is returned by the IMSL_QRSOL function.

RM, a, 4, 3 
; Define the coefficient matrix. 
   row 0:  1 2 4 
   row 1:  1 4 16 
   row 2:  1 6 36 
   row 3:  1 8 64 
RM, b, 4, 1 
; Define the right-hand side. 
   row 0:  4.999 
   row 1:  9.001 
   row 2:  12.999 
   row 3:  17.001 
x = IMSL_QRSOL(b, a) 
; Call IMSL_QRSOL. 
PM, x, Title = 'Solution', Format = '(f8.5)' 
; Output the results. 
Solution 
   0.99900 
   2.00020 
   0.00000 
PM, a # x - b, Title = 'Residual', Format = '(f10.7)' 
Residual 
    0.0004015 
   -0.0011997 
    0.0012007 
   -0.0004005

Errors

Fatal Errors

MATH_SINGULAR_TRI_MATRIX—Input triangular matrix is singular. The index of the first zero diagonal term is #.

Version History


6.4	Introduced