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Description:
This routine finds a
value which can be associated with the half- weight value. It sums all weights then finds a value for
the half-weight. The comparison with the half-weight value proceeds in halves of the weights for each
data point (half of the first weight, then the second half of the first weight and the first half of the
second weight etc.) until the half weight is exceeded. The data values around this half weight position
are then found and a linear interpolation of these values is the weighted median. The values which
contribute to the result are flagged and passed through the USED array. This routine also uses the
order statistic covariance array (for a population EL big) to estimate the change in the
variance from a optimal measurement from the given population, returning the adjusted
variance.
This version is specialised to accept bounds for the values that can be used in ARR, these are from
ARR(LBND:UBND). It is designed for use when some outliers of the population have already been
flagged for removal (say by some clipping algorithm and the variance still needs to be determined
from the original population size).
Invocation
CALL CCG_WTM4x( EL, ORDDAT, WEIGHT, VAR, LBND,
UBND, COVAR, USED, RESULT, RESVAR, STATUS )
Arguments
EL = INTEGER (Given)
The
number of entries in the data array.
ARR( EL ) = ? (Given)
The list of ordered data for which the
weighted median is required
WEIGHT( EL ) = ? (Given)
The weights of the values.
VAR
= DOUBLE PRECISION (Given)
The variance of the unordered sample now ordered
in ARR.
LBND = INTEGER (Given)
Lower bound of data to be considered in ARR.
UBND = INTEGER (Given)
Upper bound of data to be considered in ARR.
COVAR(
) =
DOUBLE PRECISION (Given)
The packed variance-covariance matrix of the order statistics from a
normal distribution of size EL.
USED( EL ) = LOGICAL (Returned)
If a value contributes to the
median value it is flagged as true in this array, otherwise the array element is set to false.
RESULT =
DOUBLE PRECISION (Returned)
The weighted median
RESVAR = DOUBLE PRECISION
(Returned)
The variance of result.
STATUS = INTEGER (Given and Returned)
The global status.
Notes:
Prior Requirements
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