NAG Library Routine Document

1Purpose

g02baf computes means and standard deviations of variables, sums of squares and cross-products of deviations from means, and Pearson product-moment correlation coefficients for a set of data.

2Specification

Fortran Interface
 Subroutine g02baf ( n, m, x, ldx, xbar, std, ssp, r, ldr,
 Integer, Intent (In) :: n, m, ldx, ldssp, ldr Integer, Intent (Inout) :: ifail Real (Kind=nag_wp), Intent (In) :: x(ldx,m) Real (Kind=nag_wp), Intent (Inout) :: ssp(ldssp,m), r(ldr,m) Real (Kind=nag_wp), Intent (Out) :: xbar(m), std(m)
#include nagmk26.h
 void g02baf_ (const Integer *n, const Integer *m, const double x[], const Integer *ldx, double xbar[], double std[], double ssp[], const Integer *ldssp, double r[], const Integer *ldr, Integer *ifail)

3Description

The input data consist of $n$ observations for each of $m$ variables, given as an array
 $xij, i=1,2,…,nn≥2,j=1,2,…,mm≥2,$
where ${x}_{ij}$ is the $i$th observation on the $j$th variable.
The quantities calculated are:
(a) Means:
 $x-j=1n∑i=1nxij, j=1,2,…,m.$
(b) Standard deviations:
 $sj=1n- 1 ∑i= 1n xij-x-j 2, j= 1,2,…,m.$
(c) Sums of squares and cross-products of deviations from means:
 $Sjk=∑i=1n xij-x-j xik-x-k , j,k=1,2,…,m.$
(d) Pearson product-moment correlation coefficients:
 $Rjk=SjkSjjSkk , j,k= 1,2,…,m.$
If ${S}_{jj}$ or ${S}_{kk}$ is zero, ${R}_{jk}$ is set to zero.

None.

5Arguments

1:     $\mathbf{n}$ – IntegerInput
On entry: $n$, the number of observations or cases.
Constraint: ${\mathbf{n}}\ge 2$.
2:     $\mathbf{m}$ – IntegerInput
On entry: $m$, the number of variables.
Constraint: ${\mathbf{m}}\ge 2$.
3:     $\mathbf{x}\left({\mathbf{ldx}},{\mathbf{m}}\right)$ – Real (Kind=nag_wp) arrayInput
On entry: ${\mathbf{x}}\left(\mathit{i},\mathit{j}\right)$ must be set to ${x}_{\mathit{i}\mathit{j}}$, the $\mathit{i}$th observation on the $\mathit{j}$th variable, for $\mathit{i}=1,2,\dots ,n$ and $\mathit{j}=1,2,\dots ,m$.
4:     $\mathbf{ldx}$ – IntegerInput
On entry: the first dimension of the array x as declared in the (sub)program from which g02baf is called.
Constraint: ${\mathbf{ldx}}\ge {\mathbf{n}}$.
5:     $\mathbf{xbar}\left({\mathbf{m}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: the mean value, ${\stackrel{-}{x}}_{\mathit{j}}$, of the $\mathit{j}$th variable, for $\mathit{j}=1,2,\dots ,m$.
6:     $\mathbf{std}\left({\mathbf{m}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: the standard deviation, ${s}_{\mathit{j}}$, of the $\mathit{j}$th variable, for $\mathit{j}=1,2,\dots ,m$.
7:     $\mathbf{ssp}\left({\mathbf{ldssp}},{\mathbf{m}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: ${\mathbf{ssp}}\left(\mathit{j},\mathit{k}\right)$ is the cross-product of deviations ${S}_{\mathit{j}\mathit{k}}$, for $\mathit{j}=1,2,\dots ,m$ and $\mathit{k}=1,2,\dots ,m$.
8:     $\mathbf{ldssp}$ – IntegerInput
On entry: the first dimension of the array ssp as declared in the (sub)program from which g02baf is called.
Constraint: ${\mathbf{ldssp}}\ge {\mathbf{m}}$.
9:     $\mathbf{r}\left({\mathbf{ldr}},{\mathbf{m}}\right)$ – Real (Kind=nag_wp) arrayOutput
On exit: ${\mathbf{r}}\left(\mathit{j},\mathit{k}\right)$ is the product-moment correlation coefficient ${R}_{\mathit{j}\mathit{k}}$ between the $\mathit{j}$th and $\mathit{k}$th variables, for $\mathit{j}=1,2,\dots ,m$ and $\mathit{k}=1,2,\dots ,m$.
10:   $\mathbf{ldr}$ – IntegerInput
On entry: the first dimension of the array r as declared in the (sub)program from which g02baf is called.
Constraint: ${\mathbf{ldr}}\ge {\mathbf{m}}$.
11:   $\mathbf{ifail}$ – IntegerInput/Output
On entry: ifail must be set to $0$, $-1\text{​ or ​}1$. 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 $-1\text{​ or ​}1$ 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 $-\mathbf{1}\text{​ or ​}\mathbf{1}$ is used it is essential to test the value of ifail on exit.
On exit: ${\mathbf{ifail}}={\mathbf{0}}$ unless the routine detects an error or a warning has been flagged (see Section 6).

6Error Indicators and Warnings

If on entry ${\mathbf{ifail}}=0$ or $-1$, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
${\mathbf{ifail}}=1$
On entry, ${\mathbf{n}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{n}}\ge 2$.
${\mathbf{ifail}}=2$
On entry, ${\mathbf{m}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{m}}\ge 2$.
${\mathbf{ifail}}=3$
On entry, ${\mathbf{ldr}}=〈\mathit{\text{value}}〉$ and ${\mathbf{m}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{ldr}}\ge {\mathbf{m}}$.
On entry, ${\mathbf{ldssp}}=〈\mathit{\text{value}}〉$ and ${\mathbf{m}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{ldssp}}\ge {\mathbf{m}}$.
On entry, ${\mathbf{ldx}}=〈\mathit{\text{value}}〉$ and ${\mathbf{n}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{ldx}}\ge {\mathbf{n}}$.
${\mathbf{ifail}}=-99$
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
${\mathbf{ifail}}=-399$
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.
${\mathbf{ifail}}=-999$
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.

7Accuracy

g02baf does not use additional precision arithmetic for the accumulation of scalar products, so there may be a loss of significant figures for large $n$.

8Parallelism and Performance

g02baf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

The time taken by g02baf depends on $n$ and $m$.
The routine uses a two-pass algorithm.

10Example

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

10.1Program Text

Program Text (g02bafe.f90)

10.2Program Data

Program Data (g02bafe.d)

10.3Program Results

Program Results (g02bafe.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017