NAG Library Function Document

nag_cov_to_corr (g02bwc)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

▸▿ 10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

1 Purpose

nag_cov_to_corr (g02bwc) calculates a matrix of Pearson product-moment correlation coefficients from sums of squares and cross-products of deviations about the mean.

2 Specification

#include <nag.h>

#include <nagg02.h>

void	nag_cov_to_corr (Integer m, double r[], NagError *fail)

3 Description

nag_cov_to_corr (g02bwc) calculates a matrix of Pearson product-moment correlation coefficients from sums of squares and cross-products about the mean for observations on

m

variables which can be computed by a single call to nag_sum_sqs (g02buc) or a series of calls to nag_sum_sqs_update (g02btc). The sums of squares and cross-products are stored in an array packed by column and are overwritten by the correlation coefficients.

Let

c_{j k}

be the cross-product of deviations from the mean, for

j = 1, 2, \dots, m

and

k = j, \dots, m

, then the product-moment correlation coefficient,

r_{j k}

is given by

r_{j k} = \frac{c_{j k}}{\sqrt{c_{j j} c_{k k}}} .

4 References

None.

5 Arguments

1: $m$ – IntegerInput: On entry: $m$ , the number of variables.

Constraint: $m \geq 1$ .
2: $r [(m \times m + m) / 2]$ – doubleInput/Output: On entry: contains the upper triangular part of the sums of squares and cross-products matrix of deviations from the mean. These are stored packed by column, i.e., the cross-product between variable $j$ and $k$ , $k \geq j$ , is stored in $r [(k \times (k - 1) / 2 + j) - 1]$ .

On exit: Pearson product-moment correlation coefficients.
These are stored packed by column corresponding to the input cross-products.
3: $fail$ – NagError *Input/Output: The NAG error argument (see Section 3.6 in the Essential Introduction).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.2.1.2 in the Essential Introduction for further information.
NE_BAD_PARAM: On entry, argument $〈value〉$ had an illegal value.
NE_INT: On entry, $m = 〈value〉$ .
Constraint: $m \geq 1$ .
NE_INTERNAL_ERROR: 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.

An unexpected error has been triggered by this function. Please contact NAG.
See Section 3.6.6 in the Essential Introduction for further information.
NE_NO_LICENCE: Your licence key may have expired or may not have been installed correctly.
See Section 3.6.5 in the Essential Introduction for further information.
NE_ZERO_VARIANCE: On entry, a variable has zero variance.

7 Accuracy

The accuracy of nag_cov_to_corr (g02bwc) is entirely dependent upon the accuracy of the elements of array r.

8 Parallelism and Performance

Not applicable.

9 Further Comments

nag_cov_to_corr (g02bwc) may also be used to calculate the correlations between parameter estimates from the variance-covariance matrix of the parameter estimates as is given by several functions in this chapter.

10 Example

A program to calculate the correlation matrix from raw data. The sum of squares and cross-products about the mean are calculated from the raw data by a call to nag_sum_sqs (g02buc). The correlation matrix is then calculated from these values.

NAG Library Function Documentnag_cov_to_corr (g02bwc)