G02BGF (PDF version)
G02 Chapter Contents
G02 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

G02BGF

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

 Contents

    1  Purpose
    7  Accuracy

1  Purpose

G02BGF computes means and standard deviations, sums of squares and cross-products of deviations from means, and Pearson product-moment correlation coefficients for selected variables.

2  Specification

SUBROUTINE G02BGF ( N, M, X, LDX, NVARS, KVAR, XBAR, STD, SSP, LDSSP, R, LDR, IFAIL)
INTEGER  N, M, LDX, NVARS, KVAR(NVARS), LDSSP, LDR, IFAIL
REAL (KIND=nag_wp)  X(LDX,M), XBAR(NVARS), STD(NVARS), SSP(LDSSP,NVARS), R(LDR,NVARS)

3  Description

The input data consist of n observations for each of m variables, given as an array
xij,  i=1,2,,nn2,j=1,2,,mm2,  
where xij is the ith observation on the jth variable, together with the subset of these variables, v1,v2,,vp, for which information is required.
The quantities calculated are:
(a) Means:
x-j=1ni=1nxij,  j=v1,v2,,vp.  
(b) Standard deviations:
sj=1n- 1 i= 1n xij-x-j 2,   j=v1,v2,,vp.  
(c) Sums of squares and cross-products of deviations from zero:
Sjk=i=1nxij-x-jxik-x-k,  j,k=v1,v2,,vp.  
(d) Pearson product-moment correlation coefficients:
Rjk=SjkSjjSkk ,   j,k=v1,v2,vp.  
If Sjj or Skk is zero, Rjk is set to zero.

4  References

None.

5  Arguments

1:     N – INTEGERInput
On entry: n, the number of observations or cases.
Constraint: N2.
2:     M – INTEGERInput
On entry: m, the number of variables.
Constraint: M2.
3:     XLDXM – REAL (KIND=nag_wp) arrayInput
On entry: Xij must be set to xij, the value of the ith observation on the jth variable, for i=1,2,,n and j=1,2,,m.
4:     LDX – INTEGERInput
On entry: the first dimension of the array X as declared in the (sub)program from which G02BGF is called.
Constraint: LDXN.
5:     NVARS – INTEGERInput
On entry: p, the number of variables for which information is required.
Constraint: 2NVARSM.
6:     KVARNVARS – INTEGER arrayInput
On entry: KVARj must be set to the column number in X of the jth variable for which information is required, for j=1,2,,p.
Constraint: 1KVARjM, for j=1,2,,p.
7:     XBARNVARS – REAL (KIND=nag_wp) arrayOutput
On exit: the mean value, x-j, of the variable specified in KVARj, for j=1,2,,p.
8:     STDNVARS – REAL (KIND=nag_wp) arrayOutput
On exit: the standard deviation, sj, of the variable specified in KVARj, for j=1,2,,p.
9:     SSPLDSSPNVARS – REAL (KIND=nag_wp) arrayOutput
On exit: SSPjk is the cross-product of deviations, Sjk, for the variables specified in KVARj and KVARk, for j=1,2,,p and k=1,2,,p.
10:   LDSSP – INTEGERInput
On entry: the first dimension of the array SSP as declared in the (sub)program from which G02BGF is called.
Constraint: LDSSPNVARS.
11:   RLDRNVARS – REAL (KIND=nag_wp) arrayOutput
On exit: Rjk is the product-moment correlation coefficient, Rjk, between the variables specified in KVARj and KVARk, for j=1,2,,p and k=1,2,,p.
12:   LDR – INTEGERInput
On entry: the first dimension of the array R as declared in the (sub)program from which G02BGF is called.
Constraint: LDRNVARS.
13:   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).

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:
IFAIL=1
On entry,N<2.
IFAIL=2
On entry,NVARS<2,
orNVARS>M.
IFAIL=3
On entry,LDX<N,
orLDSSP<NVARS,
orLDR<NVARS.
IFAIL=4
On entry,KVARj<1,
orKVARj>M for some j=1,2,,NVARS.
IFAIL=-99
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.
IFAIL=-399
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.
IFAIL=-999
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.

7  Accuracy

G02BGF does not use additional precision arithmetic for the accumulation of scalar products, so there may be a loss of significant figures for large n.

8  Parallelism and Performance

G02BGF is not threaded in any implementation.

9  Further Comments

The time taken by G02BGF depends on n and p.
The routine uses a two pass algorithm.

10  Example

This example reads in a set of data consisting of five observations on each of four variables. The means, standard deviations, sums of squares and cross-products of deviations from means, and Pearson product-moment correlation coefficients for the fourth, first and second variables are then calculated and printed.

10.1  Program Text

Program Text (g02bgfe.f90)

10.2  Program Data

Program Data (g02bgfe.d)

10.3  Program Results

Program Results (g02bgfe.r)


G02BGF (PDF version)
G02 Chapter Contents
G02 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2016