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### GENERATE_CORRELATED_DATA

GENERATE_CORRELATED_DATA

## Name

GENERATE_CORRELATED_DATA

## Purpose

This function will return a list of k normally-distributed,
correlated, n-dimensional random points [with a specified
mean vector and set of univariate standard deviations].

Statistics.

## Calling Sequence

Result = \$
GENERATE_CORRELATED_DATA, seed,
numberPoints,
correlationMatrix,
MEAN_VECTOR=meanVector,
STANDARD_DEVIATION=standardDeviation,

## Inputs

seed
A variable or constant (long integer) used to initialize
the random sequence on input, and in which the state of the
random number generator is saved on output.
numberPoints
A variable or constant containing the number of n-dimensional
values to be produced.
correlationMatrix
A two-dimensional matrix describing the correlation to be
exhibited between variables. This matrix will also define
the dimensionality of the produced data set (for example, a
3x3 correlation matrix will cause 3-dimensional data to be
generated).

## Keyword Parameters

MEAN_VECTOR
A vector defining the mean for each dimension of the generated
data set. If omitted, the mean vector will be filled with 0's.
STANDARD_DEVIATION
A vector defining the standard deviation for each dimension of
the generated data set. If omitted, the standard deviation vector
will be filled with 1's.

## Return Value

A matrix containing multi-dimensional, normally-distributed,
correlated random values. The random values will be contained
in the rows of the returned matrix.

If the dimensions of the provided descriptive statistics are
incompatible, a scaler value of -1 will be returned.

If the dimensions of the data set, as determined from the
provided correlation matrix is less than 2, then a scalar
value of -2 will be returned.

## Side Effects

If the seed is specifed as any data type besides a long integer, it
will be truncated and changed to this data type.

## Modification History

Written by: Carl Salvaggio
April, 2009 Original code

## Disclaimer

This source code is provided "as is" and without warranties as to performance
or merchantability. The author and/or distributors of this source code may