NAG Library Routine Document

g10zaf (data_order)


g10zaf orders and weights data which is entered unsequentially, weighted or unweighted.


Fortran Interface
Subroutine g10zaf ( weight, n, x, y, wt, nord, xord, yord, wtord, rss, iwrk, ifail)
Integer, Intent (In):: n
Integer, Intent (Inout):: ifail
Integer, Intent (Out):: nord, iwrk(n)
Real (Kind=nag_wp), Intent (In):: x(n), y(n), wt(*)
Real (Kind=nag_wp), Intent (Out):: xord(n), yord(n), wtord(n), rss
Character (1), Intent (In):: weight
C Header Interface
#include <nagmk26.h>
void  g10zaf_ (const char *weight, const Integer *n, const double x[], const double y[], const double wt[], Integer *nord, double xord[], double yord[], double wtord[], double *rss, Integer iwrk[], Integer *ifail, const Charlen length_weight)


Given a set of observations xi,yi, for i=1,2,,n, with corresponding weights wi, g10zaf rearranges the observations so that the xi are in ascending order.
For any equal xi in the ordered set, say xj=xj+1==xj+k, a single observation xj is returned with a corresponding y and w, calculated as
y=l= 0kwi+lyi+l w .  
Observations with zero weight are ignored. If no weights are supplied by you, then unit weights are assumed; that is wi=1, for i=1,2,,n.
In addition, the within group sum of squares is computed for the tied observations using West's algorithm (see West (1979)).


Draper N R and Smith H (1985) Applied Regression Analysis (2nd Edition) Wiley
West D H D (1979) Updating mean and variance estimates: An improved method Comm. ACM 22 532–555


1:     weight – Character(1)Input
On entry: indicates whether user-defined weights are to be used.
  • If weight='W', user-defined weights are to be used and must be supplied in wt.
  • If weight='U', the data is treated as unweighted.
Constraint: weight='W' or 'U'.
2:     n – IntegerInput
On entry: n, the number of observations.
Constraint: n1.
3:     xn – Real (Kind=nag_wp) arrayInput
On entry: the values, xi, for i=1,2,,n.
4:     yn – Real (Kind=nag_wp) arrayInput
On entry: the values yi, for i=1,2,,n.
5:     wt* – Real (Kind=nag_wp) arrayInput
Note: the dimension of the array wt must be at least n if weight='W'.
On entry: if weight='W', wt must contain the n weights. Otherwise wt is not referenced and unit weights are assumed.
  • if weight='W', wti0.0, for i=1,2,,n;
  • if weight='W', i=1nwti>0.
6:     nord – IntegerOutput
On exit: the number of distinct observations.
7:     xordn – Real (Kind=nag_wp) arrayOutput
On exit: the first nord elements contain the ordered and distinct xi.
8:     yordn – Real (Kind=nag_wp) arrayOutput
On exit: the first nord elements contain the values y corresponding to the values in xord.
9:     wtordn – Real (Kind=nag_wp) arrayOutput
On exit: the first nord elements contain the values w corresponding to the values of xord and yord.
10:   rss – Real (Kind=nag_wp)Output
On exit: the within group sum of squares for tied observations.
11:   iwrkn – Integer arrayWorkspace
12:   ifail – IntegerInput/Output
On entry: ifail must be set to 0, -1 or 1. If you are unfamiliar with this argument you should refer to Section 3.4 in How to Use the NAG Library and its Documentation for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1 or 1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this argument, the recommended value is 0. When the value -1 or 1 is used it is essential to test the value of ifail on exit.
On exit: ifail=0 unless the routine detects an error or a warning has been flagged (see Section 6).

Error Indicators and Warnings

If on entry ifail=0 or -1, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
On entry, n=value.
Constraint: n1.
On entry, weight=value.
Constraint: weight='W' or 'U'.
On entry, all weights are zero.
On entry, i=value and wti=value.
Constraint: wti0.0.
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 3.8 in How to Use the NAG Library and its Documentation for further information.
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.


For a discussion on the accuracy of the algorithm for computing mean and variance see West (1979).

Parallelism and Performance

g10zaf is not threaded in any implementation.

Further Comments

g10zaf may be used to compute the pure error sum of squares in simple linear regression along with g02daf; see Draper and Smith (1985).


A set of unweighted observations are input and g10zaf used to produce a set of strictly increasing weighted observations.

Program Text

Program Text (g10zafe.f90)

Program Data

Program Data (g10zafe.d)

Program Results

Program Results (g10zafe.r)