g01dcc computes an approximation to the variance-covariance matrix of an ordered set of independent observations from a Normal distribution with mean

0.0

and standard deviation

1.0

2 Specification

#include <nag.h>

void	g01dcc (Integer n, double exp1, double exp2, double sumssq, double vec[], NagError *fail)

The function may be called by the names: g01dcc, nag_stat_normal_scores_var or nag_normal_scores_var.

3 Description

g01dcc is an adaptation of the Applied Statistics Algorithm AS 128, see Davis and Stephens (1978). An approximation to the variance-covariance matrix,

V

, using a Taylor series expansion of the Normal distribution function is discussed in David and Johnson (1954).

However, convergence is slow for extreme variances and covariances. The present function uses the David–Johnson approximation to provide an initial approximation and improves upon it by use of the following identities for the matrix.

For a sample of size

n

, let

m_{i}

be the expected value of the

i

th largest order statistic, then:

(a)for any $i = 1, 2, \dots, n$ , $\sum_{j = 1}^{n} V_{i j} = 1$
(b) $V_{12} = V_{11} + m_{n}^{2} - m_{n} m_{n - 1} - 1$
(c)the trace of $V$ is $t r (V) = n - \sum_{i = 1}^{n} m_{i}^{2}$
(d) $V_{i j} = V_{j i} = V_{r s} = V_{s r}$ where $r = n + 1 - i$ , $s = n + 1 - j$ and $i, j = 1, 2, \dots, n$ . Note that only the upper triangle of the matrix is calculated and returned column-wise in vector form.

4 References

David F N and Johnson N L (1954) Statistical treatment of censored data, Part 1. Fundamental formulae Biometrika 41 228–240

Davis C S and Stephens M A (1978) Algorithm AS 128: approximating the covariance matrix of Normal order statistics Appl. Statist. 27 206–212

5 Arguments

1: $n$ – Integer Input: On entry: $n$ , the sample size.

Constraint: $n > 0$ .
2: $exp1$ – double Input: On entry: the expected value of the largest Normal order statistic, $m_{n}$ , from a sample of size $n$ .
3: $exp2$ – double Input: On entry: the expected value of the second largest Normal order statistic, $m_{n - 1}$ , from a sample of size $n$ .
4: $sumssq$ – double Input: On entry: the sum of squares of the expected values of the Normal order statistics from a sample of size $n$ .
5: $vec [n \times (n + 1) / 2]$ – double Output: On exit: the upper triangle of the $n \times n$ variance-covariance matrix packed by column. Thus element $V_{i j}$ is stored in $vec [i + j \times (j - 1) / 2 - 1]$ , for $1 \leq i \leq j \leq n$ .
6: $fail$ – NagError * Input/Output: The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM: On entry, argument $⟨ value ⟩$ had an illegal value.
NE_INT: On entry, $n = ⟨ value ⟩$ .
Constraint: $n > 0$ .
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.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.

7 Accuracy

For

n \leq 20

, where comparison with the exact values can be made, the maximum error is less than

0.0001

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

g01dcc is not threaded in any implementation.

9 Further Comments

The time taken by g01dcc is approximately proportional to

n^{2}

The arguments

exp1

(

= m_{n}

exp2

(

= m_{n - 1}

) and

sumssq

(

= \sum_{j = 1}^{n} m_{j}^{2}

) may be found from the expected values of the Normal order statistics obtained from g01dac .

10 Example

A program to compute the variance-covariance matrix for a sample of size

6

. g01dac is called to provide values for exp1, exp2 and sumssq.

10.1 Program Text

Program Text (g01dcce.c)

10.2 Program Data

None.

10.3 Program Results

Program Results (g01dcce.r)

NAG Library Manual, Mark 29.2

Interfaces: FL CL CPP AD PY MB

NAG CL Interface Introduction

G01 (Stat) Chapter Contents

G01 (Stat) Chapter Introduction

g01dc: FL CL CPP AD PY MB

NAG CL Interfaceg01dcc (normal_​scores_​var)

▸▿ Contents

1 Purpose