## Computational Resources

The MODECLUS procedure stores coordinate data
in memory if there is enough space.
For distance data, only one observation at a time is in memory.
PROC MODECLUS constructs lists of the
neighbors of each observation.
The total space required is
bytes, where
*n*_{i} is based on the largest
neighborhood required by any analysis.
The lists are stored in a SAS utility
data set unless you specify the CORE option.
You may get an error message from the SAS System
or from the operating system
if there is not enough disk space for the utility data set.
Clustering method 6 requires a second list that is always stored in memory.

For coordinate data, the time required to construct the
neighbor lists is roughly proportional to
.For distance data, the time is roughly proportional to
.

The time required for density estimation is proportional to
and is usually small compared to the time
required for constructing the neighbor lists.

Clustering methods 0 through 3 are quite efficient, requiring
time proportional to . Methods 4 and 5 are slower,
requiring time roughly proportional to
.Method 6 can also be slow, but the time requirements
depend very much on the data and the particular options specified.
Methods 4, 5, and 6 also require more memory than the other
methods.

The time required for significance tests is roughly
proportional to ,where *g* is the number of clusters.

PROC MODECLUS can process data sets of several thousand
observations if you specify reasonable smoothing parameters.
Very small smoothing values produce many clusters, whereas
very large values produce many neighbors; either case can require
excessive time or space.

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.