nag_normal_scores_var (g01dcc) computes an approximation to the variance-covariance matrix of an ordered set of independent observations from a Normal distribution with mean and standard deviation .
nag_normal_scores_var (g01dcc) is an adaptation of the Applied Statistics Algorithm AS 128, see
Davis and Stephens (1978). An approximation to the variance-covariance matrix,
, 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
, let
be the expected value of the
th largest order statistic, then:
(a) |
for any , |
(b) |
|
(c) |
the trace of is |
(d) |
where , and . Note that only the upper triangle of the matrix is calculated and returned column-wise in vector form. |
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
Not applicable.
The time taken by nag_normal_scores_var (g01dcc) is approximately proportional to .
The arguments
(
),
(
) and
(
) may be found from the expected values of the Normal order statistics obtained from
nag_normal_scores_exact (g01dac)
.
A program to compute the variance-covariance matrix for a sample of size
.
nag_normal_scores_exact (g01dac) is called to provide values for
exp1,
exp2 and
sumssq.
None.